- Comp-neuro - lists.cnsorg.org

Neurodata Without Borders (NWB) User Days Workshop - September 21-23
by Ryan Ly Aug. 17, 2020

Aug. 17, 2020

Neurodata Without Borders (NWB) is a data standard for neurophysiology, providing neuroscientists with a common standard to share, archive, use, and build analysis tools for neurophysiology data. NWB is designed to store a variety of neurophysiology data, including data from intracellular and extracellular electrophysiology experiments, data from optical physiology experiments, behavioral data, and stimulus data. The NWB Team will be hosting the 9th NWB User Days Workshop remotely on September 21-23. The workshop schedule will be centered on Central European Time (UTC+2) and will focus primarily on user training, including lessons for complete beginners to NWB. Come learn how to get your data into the NWB data standard and use state-of-the-art data analysis, visualization, and management tools with NWB, e.g., Brainstorm, CaImAn, calciumImagingAnalysis, DANDI, DataJoint, MIES, NWB Explorer, NWB Widgets, SpikeInterface, and suite2p. Event page: https://neurodatawithoutborders.github.io/nwb_hackathons/HCK09_2020_Remote/ Register here: https://bit.ly/2PHbE34 (it's free) Learn more about NWB at our website: https://www.nwb.org/ Best, The NWB Team -- Ryan Ly Scientific Data Engineer Lawrence Berkeley National Laboratory 1 Cyclotron Road Mail Stop 59R4104 Berkeley, CA 94720 Email: rly(a)lbl.gov Pronouns: he/him

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Neural Data Analysis Online Course
by Maryam Aug. 17, 2020

Aug. 17, 2020

You are invited to “Neural Data Analysis Online Course” Dear Sir, Madam; ScienceBeam, which is a forefront technology provider of neuroscience applications, would like to take the opportunity to invite you for 10-session “Neural Data Analysis Online Course” that is going to start on September 7, 2020. During this course you will learn: ( Programming fundamentals: Variables, plots, loops ( How to compare ERPs in a statistical way: confidence intervals and bootstrapping ( EEG spectrum and spectrogram: from time to frequency and time-frequency ( More on spectrum: windowing and zero padding ( Analysis of coupled rhythms: covariance and coherence ( Filtering, filtering, and filtering! ( Cross-frequency coupling and Hilbert transform ( Brain states in sleep and Hidden Markov Model Hamed Yeganegi, PhD researcher in systems neuroscience, Technical University of Munich, Germany, is the instructor of this course. He is also a member of German Neuroscience Society (NWG) and Member of Federation of European Neuroscience Societies (FENS). Registration is open until September 4th. You won’t want to miss this! Don’t hesitate and register from the link below: Register NOW ! If you needed more information please contact us via Whatsapp or Mail: Whatsapp number: +86 133 8078 1282 Email: workshop(a)sciencebeam.com www.sciencebeam.com

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One Fellow position for closed-loop systems in neuroengineering @IIT Genova, ITALY
by Michela Chiappalone Aug. 17, 2020

Aug. 17, 2020

Dear Comp-Neuro community, A new opening for a 12-months fellowship position at the Pre-Doctoral level is available in our team, under the supervision of Dr Stefano Buccelli and myself at the Rehab Technologies Lab of the Istituto Italiano di Tecnologia (IIT), located in Genova at the IIT Center for Convergent Technologies. The fellow will carry out research on the development of a novel closed-loop architecture for applications in neuroengineering. More information on the position can be found below in this email. The application link can be found here: https://iit.taleo.net/careersection/ex/jobdetail.ftl?lang=en&job=2000002C The call expires on September 7th, 2020. Please forward this message to all the interested students. Thank you and best regards, Michela Chiappalone & Stefano Buccelli ---------------------------------------------------------------------------------------------------------------------------------------------------------------- One Fellow position for the development of a reference architecture for closed-loop systems for neuroengineering applications The Rehab Technologies INAIL-IIT lab, (http://rehab.iit.it/) at Istituto Italiano di Tecnologia (IIT), Genova, Italy, is seeking to appoint one Fellow at the pre-Doctoral level to carry out research on the development of novel closed-loop architecture for applications in neuroengineering. The Rehab Technologies Lab is an innovation lab aimed at developing new high tech prosthetic, orthotic and rehabilitation devices of high social impact and market potential. The Lab is primarily focused on disability and rehabilitation, and exploits a co-creation process which involves scientists, patients and therapists in all the phases of the design, realization and testing of devices developed within the lab. The Neuroengineering area of Rehab Technologies is focused on neural interfaces and neurorehabilitation. The team has a multidisciplinary expertise in engineering and neuroscience, with skills in in vitro/in vivo electrophysiology, signal processing of neural data (spikes, LFP, EEG), closed-loop systems, neurostimulation and innovative neuroprostheses. The primary research goals of the team consist of designing and testing novel 'personalized' neuroengineering solutions for brain repair and extracting functional biomarkers of recovery induced by the rehab-related training. In modern neuroscience, closed-loop systems delivering stimulation depending on to the actual brain state demonstrated to improve the efficacy of a therapy, also reducing the number of side effects. To build a closed-loop system, three steps are needed: reading, interpreting and writing the neural code. To 'read' the neural code, we need to record neural activity, by using either invasive or non-invasive techniques. 'Interpreting' or decoding the neural activity is obtained by means of (real-time) signal processing techniques. To 'write' the neural code, usually an electrical simulation approach is adopted (but other options are available). Nowadays, given the increased number of recording sites that can be acquired at the same time, there is a big demand for high-performance signal processing techniques in both clinical practice and basic research. Field-Programmable Gate Arrays (FPGA) are one of the most interesting options for the implementation of high-performance computations and are usually chosen as a first step towards the development of standalone devices. Learning how to implement an algorithm on FPGA can be prohibitive for non-experts and thus it is preventing many neuroscientists from realizing innovative closed-loop systems. Within this framework and to reduce the entry barrier in the development of closed-loop architectures on FPGA, this project will built up a rapid-prototyping, reference architecture for closed-loop neuroengineering applications by exploiting a model-based design approach (in Simulink). This will be reached by means of the following specific objectives: 1. Build a reference Simulink model to process neural data. 2. Take advantage of the HDL coder and the Fixed-Point Designer to implement the model on FPGA; 3. Establish use cases on commercially available systems (e.g. INTAN Stimulation/Recording system). The project will be carried out at the Rehab Technologies Lab of IIT, located in Genova at IIT Center for Convergent Technologies. To face this technological challenge, the Rehab Technologies Lab will share resources, competencies and motivation to achieve excellent results transferable to the neuroengineering field and, later, to clinics. We are looking for a highly motivated, outstanding candidate with the following profile: - A solid background in biomedical/electronics engineering - Strong programming skills, especially with the MathWorks products (Matlab, Simulink) - Master Degree in one of the above field (already obtained or to be obtained in the next two months) - Good communication skills and ability to cooperate - Proficiency in English Desirable skills: - Experience with Verilog/VHDL During this period, the selected candidate will develop the following skills and experience: - Principle of Neuroengineering and its applications - Model-based Design and Rapid Prototyping - Closed-loop architectures - Basic Electrophysiological skills - Interactions within a multidisciplinary Lab and for an International project To apply, please send your CV, title of the Master Thesis and (foreseen) date of graduation, cover letter and name and contacts of one/two referees using the form online. Deadline: September 7, 2020. Istituto Italiano di Tecnologia (IIT), with its headquarters in Genova, Italy, is a non-profit institution with the primary goal of creating and disseminating scientific knowledge and strengthening Italy's technological competitiveness. The institute offers state-of-the-art equipment and a top-level interdisciplinary research environment focused on robotics and computer vision, neuroscience, drug discovery, nanoscience and technology. Istituto Italiano di Tecnologia is an Equal Opportunity Employer that actively seeks diversity in the workforce. Please note that the data that you provide will be used exclusively for the purpose of professional profiles' evaluation and selection, and in order to meet the requirements of Istituto Italiano di Tecnologia. Your data will be processed by Istituto Italiano di Tecnologia, based in Genoa, Via Morego 30, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security. Please also note that, pursuant to articles 15 et. seq. of European Regulation no. 679/2016 (General Data Protection Regulation), you may exercise your rights at any time by contacting the Data Protection Officer (phone +39 010 71781 - email: dpo[at]iit.it). ------------------------------------------------------------------------- Dr Michela Chiappalone, PhD Researcher Rehab Technologies IIT-INAIL Lab Phone : +39 010 71781743 E-mail : michela.chiappalone(a)iit.it<mailto:michela.chiappalone@iit.it> ISTITUTO ITALIANO DI TECNOLOGIA Via Morego 30, 16163 Genova Site: www.iit.it<http://www.iit.it>

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Web Conference /DMSE 2020, Denmark - Deadline Approaching[Third Batch Call for Submissions] .
by Fredrick Johnson Aug. 13, 2020

Aug. 13, 2020

International Conference on Data Mining and Software Engineering (DMSE 2020) September 26 ~ 27, 2020, Copenhagen, Denmark *WIKICFP Call* : http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=111118&copyownerid… *DBWORLD Call* : http://www.cs.wisc.edu/dbworld/messages/2020-08/1597292447.html Scope & Topics International Conference on Data Mining and Software Engineering (DMSE 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Data mining and Software Engineering. The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on understanding Data mining and modern software engineering concepts and establishing new collaborations in these areas. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of data mining and software engineering. Topics of interest include, but are not limited to, the following • Advanced Topics in Software Engineering • Data Mining Applications • Computer Education • Data Mining in Modeling, Visualization, Personalization and Recommendation • Data Mining Systems and Platforms, Efficiency, Scalability and Privacy • Embedded System and Software • Foundations, Algorithms, Models, and Theory • Knowledge Processing • Knowledge-based Systems and Formal Methods • Languages and Formal Methods • Managing Software Projects • Mining Text, Semi-Structured, Spatio-Temporal, Streaming, Graph, Web, Multimedia • Multimedia and Visual Software Engineering • Quality Management • Search Engines and Information Retrieval • Software Engineering Decision Making • Software Engineering Practice • Software Maintenance and Testing • Software Process • Web Engineering • Web-based Education Systems and Learning Applications Accepted Papers List Learning for E-Learning-Aalen University, Germany. Magnetic Resonance Image Classification of Major Depression Disorder Based on Deep Learning-Beijing Technology and Business University, Beijing, China COSM: Controlled Over-sampling Method. A Methodological Proposal to Overcome the Class Imbalance Problem in Data Mining-CIRA (Italian Aerospace Research Centre),Italy A Process for Complete Autonomous Software Display Validation And Testing (Using A Car-cluster)-SAP Labs India Pvt Lmt.,India Analysis of the Displacement of Terrestrial Mobile Robots in Corridors Using Paraconsistent Annotated Evidential Logic Et-Bialystok University of Technology,Poland A Study on the Minimum Requirements for the On-line, Efficient and Robust Validation of Neutron Detector Operation and Monitoring of Neutron Noise Signals using Harmony Theory Networks-University of Piraeus, France Penalized Bootstrapping for Reinforcement Learning in Robot Control-University of Bonn,Germany Deep Reinforcement Learning for Navigation in Cluttered Environments-University of Bonn, Germany New Hybrid Artificial Intelligent Models Basedon Optimized-support Vector Machine and Locallylinear Neuro fuzzy for the Supplier Assessment Problem-Islamic Azad University, Iran IoT Learning Model for Smart Universities: Architecture, Challenges, and Applications-Whitecliffe College of Technology & Innovation, New Zealand The Principles of the Law General on the Protection of Personal Data and their Importance-Paulista University, Brazil. Controlled Machine Text Generation of Football Articles-University of Warsaw, Poland On the Comparison of Deep Neural Networks for Document Retrieval-Institute for Community Medicine, Germany Evaluationn of Company Investment value based on Machine Learning-Beijing University of Technology, China Performance evaluation of Precoded Band Codes and Hamming Norm Decoders in Random Linear Network Coding-National Engineering School of Tunis, Tunisia Neurological Signals Compression and Encryption for Security Transmission Based on IOMT: A Tele-neurological Diagnosis-University of Anbar, Iraq. Paper Submission Authors are invited to submit papers through the conference Submission System . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed). Here’s where you can reach us : dmse(a)dmse2020.org or dmsesecretary(a)gmail.com Submit your work Today! Regards, Fredrick.

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Post-doctoral Research position at Johns Hopkins BME
by Adam Charles Aug. 11, 2020

Aug. 11, 2020

Dear Comp-neuro community: Please see below for a post-doctoral opportunity in my lab at The Johns Hopkins University Department of Biomedical Engineering. Link: https://www.bme.jhu.edu/ascharles/open-positions/ Warmest regards, -Adam ----------------------- Adam S. Charles Assistant Professor Department of Biomedical Engineering The Johns Hopkins University Baltimore, MD, 21218 ----------------------------------------------------------------------------------- I am pleased to announce a postdoctoral position in computational imaging, computational neuroscience and data science at the Johns Hopkins University Department of Biomedical Engineering in the lab of Adam Charles. This project is aimed at advancing the capabilities of functional fluorescence microscopy for neural recordings via new computational tools, including machine learning “at the sensor” and machine learning/signal processing for image analysis and interpretation. Neural imaging is an exciting field and this position offers opportunities to develop a range of new models and algorithms to address the unique challenges in fast and accurate fluorescence imaging and analysis. In addition, this project offers opportunities to interface with experimental collaborators. Applicants should hold a PhD in Engineering, Mathematics, Physics, Neuroscience or a related field with a strong research record. Applications should have demonstrated the ability to work collaboratively on quantitative problems. Applicants with experience in machine learning, signal processing, compressive sensing, computational imaging or computational neuroscience are especially encouraged to apply. Excellent written and oral communication skills in English are also required. This position is open immediately and will remain open until filled. The position is initially for 12 months with the possibility and expectation of renewal. Compensation will be commensurate with relevant experience. Candidates should send a CV, a statement of research experience and interests, expected date of availability, and the contact information for three references to adamsc(a)jhu.edu with the subject line "Computational imaging postdoc". Applications will be reviewed on a rolling basis and should be received by September 1 for full consideration. If the current COVID19 situation will delay the ability to apply by this deadline, please send a short note indicating that you intend to apply. Johns Hopkins University is a leader in biomedical engineering, imaging science, and neuroscience. The Department of Biomedical Engineering at Hopkins, along with the Center for Imaging Science (CIS), Kavli Institute for Neuroscience and Mathematical Institute for Data Science (MINDS) form a strong interdisciplinary computational community. JHU has competitive benefits (including comprehensive medical insurance) and is an equal opportunity employer.

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PhD position on human resource rationality
by Dominik Endres Aug. 11, 2020

Aug. 11, 2020

We offer a PhD position in the research training group RTG 2271 "Breaking Expectations" https://www.uni-marburg.de/en/fb04/rtg-2271[1] in the department of Psychology at the Philipps-Universität Marburg. In this sub-project, we investigate whether individual humans are Bayesian resource- rational learners under naturalistic conditions where possible (virtual reality), and in online experiments. Specifically, we will compare the learning dynamics of these models and their dealing with expectation violations to human behavior. One possible application direction are models of chronic and acute pain perception and prediction. The project requires a keen interest in the computational and mathematical modeling of human experimental data. Interest in designing and carrying out such experiments is a plus. Benefits of membership in the GRK 2271 include: - scientific exchange with a vibrant community of PhD students and PIs of the other projects - possibility of (funded) lab visits with international mentors/collaborators - yearly retreats in the scenic Kleinwalsertal Formal requirements are: * a qualified degree in psychology, or computer science, or cognitive science, or engineering, or physics (Master, Diploma, or comparable) as well as * demonstrable programming experience in a high-level language, e.g. Python or Matlab. We expect you to be interested in: * the topic of the project (to be documented in a motivation letter [1 page max], in which you may refer to prior experiences, for instance, a thematically pertinent thesis, student research assistant positions, etc.) * quantitative modeling * developing virtual-reality scenarios and technology for research purposes Advantageous qualifications are: * prior exposure to machine learning, associative, Bayesian or other mathematical learning models and Bayesian statistics * willing to learn basic German language skills Application deadline: 28.08.20 For further information, please contact Prof. Dominik Endres (dominik.endres@uni- marburg.de[2]). The official job advert can be found here (deadline has been extended to 28.08.20): https://www.uni-marburg.de/de/universitaet/administration/verwaltung/dezern… personalabteilung/bewerber/stellen/wissenschaftliche-stellen/fb04-0026-wmz-310720- engl.pdf[3] -- Prof. Dr. Dominik Endres AE Theoretische Kognitionswissenschaft Allgemeine und Biologische Psychologie FB Psychologie, Gutenbergstr 18, 35032 Marburg, Germany Tel. +49-(0)6421-28-23818 -------- [1] https://www.uni-marburg.de/en/fb04/rtg-2271/beschreibung [2] mailto:dominik.endres@uni-marburg.de [3] https://www.uni-marburg.de/de/universitaet/administration/verwaltung/dezern… personalabteilung/bewerber/stellen/wissenschaftliche-stellen/fb04-0026-wmz-310720- engl.pdf

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Senior Scientist – Stroke position at the NeuroRestore center (Lausanne, Switzerland)
by Milekovic Tomislav Aug. 9, 2020

Aug. 9, 2020

Senior Scientist – Stroke position at the NeuroRestore center (Lausanne, Switzerland) Location The Defitech Center for interventional Neurotherapies (NeuroRestore) is a research and innovation center joining EPFL’s lab of Prof. Gregoire Courtine and the University Hospital of Lausanne (CHUV) lab of Prof. Jocelyne Bloch. We conceive, develop and apply medical therapies aimed to restore neurological functions. To this end, we integrate implantable neurotechnologies with innovative treatments developed through rigorous preclinical and clinical studies. By working with our network of vibrant high-tech start-ups and established medical technology companies, we are committed to validate our medical therapy concepts. Our overarching goal is to see our medical therapies used every day in hospitals and rehabilitation clinics worldwide. Opportunity Over the last decade, research labs under the NeuroRestore umbrella have achieved breakthroughs for the treatment of spinal cord injury and Parkinson’s disease. Our recent studies indicate that similar approaches may lead to novel therapies for stroke. Therefore, we decided to build a strong research core focused on gaining deeper understanding of stroke and resulting neurological deficits, and on developing therapies that leverage the gained understanding to replace or restore motor functions impacted by stroke. By integrating well-equipped and expertly staffed rodent, non-human primate and clinical research facilities, NeuroRestore provides an ideal substrate for rapidly developing, integrating and clinically validating cutting-edge concepts of medical therapies, with the capacity to push successfully proven concepts into the technology transition phase. Position Summary The Senor Scientist – Stroke will bring their expertise and experience to build and then lead the stroke research core of the NeuroRestore center. They will develop original research projects across the whole stroke therapy development spectrum, starting from mechanistic understanding of stroke and resulting neurological and motor deficits, over preclinical tests of therapy concepts designed to take advantage of uncovered mechanisms, to clinical validation of therapies designed to alleviate motor deficits secondary to stroke. They will form and lead teams of NeuroRestore postdoctoral scientists, doctoral students, engineers and clinicians to execute these projects. They will train other scientists in their expert techniques and supervise junior scientists working on their projects. They will disseminate the results of their projects through research publications and conference talks and support preparation of scientific conference presentations and publications of other NeuroRestore personnel that works on stroke-related projects. They will take part in writing grant application that will support stroke-related projects. Responsibilities - Identify unmet clinical needs of stroke survivors and monitor the development of the medical neurotech sector to find opportunities for novel, feasible and rapidly realizable stroke therapies - Conceive, organize and plan out research projects - Form and leads teams to execute conceived research projects - Utilize their academic / clinical industry network to form collaborations that will help execute conceived research projects - Assess the project needs, identify relevant personnel and resources, and take part in hiring technical and scientific personnel to build skilled project teams - Train the NeuroRestore personnel in their area of expertise - Run project progress meetings, report on project progress, plan and manage the dissemination of project results - Take part in writing of funding applications to initiate new projects, strengthen / accelerate ongoing projects, or enhance ongoing collaborations - Develop and maintain connections with science labs and clinical centers to facilitate rapid animal and clinical testing of concepts and prototypes of medical treatments - Manage efforts to obtain regulatory approvals for animal studies and clinical trials to validate the concepts of medical therapies - Represent the Neurorestore Center at symposiums and conferences through talks and presentations Personal Traits - Passionate about the development of neurotechnologies that aim to alleviate movement disabilities of stroke - Thriving in a cutting edge, fast-paced, multidisciplinary environment - Self-starter and independent worker with an ability to identify innovative approaches and solutions - Attention to detail - Independent thinker and passionate problem solver Skills - Ability to independently conceive original research projects - Capacity to supervise several research projects in parallel - Capability to successfully lead research teams, and maintain collaborations with external partners - Strong verbal and written presentation skills in English - Experience with leading animal research projects and/or projects under the framework of clinical trials and studies - Track record of obtaining regulatory approvals for animal studies and/or clinical trials - Strong experience with writing project proposals, project progress reports and research articles - Experience in disseminating project progress through talks, presentation and publications - Experience in physiological signal acquisition and signal analysis - Capacity to identify skill gaps and hire personnel to fill them - Experience with writing, filling and obtaining patents - Advanced presentation skills (PowerPoint, Photoshop, Illustrator) - Willingness to travel in order to form / maintain collaborations - Possessing a strong academic, clinical, regulatory and industry network and the ability to use it to organize collaborative projects Experience - Doctoral degree (PhD) - 6 or more years of experience working in the fields of neuroscience / neuroengineering (including the PhD studies) - 3 or more years of experience in stroke-related research - Strong publication record in the stroke field Contact Applications including a CV and a cover letter describing your background and interest should be sent to tomislav.milekovic(a)epfl.ch<mailto:tomislav.milekovic@epfl.ch>. Informal inquiries are welcome.

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PhD position in machine learning at EPFL (Lausanne, Switzerland)
by Milekovic Tomislav Aug. 9, 2020

Aug. 9, 2020

PhD position in the lab of Prof. Gregoire Courtine at EPFL (Lausanne, Switzerland) Machine learning techniques to develop and enhance computational models of the spinal cord Location: The laboratory of Prof. Gregoire Courtine at the Swiss Federal Institute of Technology (EPFL) in Lausanne, Switzerland, is looking to fill a fully funded PhD position. The qualified candidate will benefit from joining a very dynamic and multidisciplinary group working at the interface of computational neuroscience, neuroengineering, prosthetics and biology. EPFL provides state-of-the-art facilities and is one of the leading technical universities worldwide. PhD salaries at EPFL rank the highest in the world. Opportunity: The offered position will be based at the Defitech Center for interventional Neurotherapies (NeuroRestore) - a research and innovation center joining EPFL's lab of Prof. Gregoire Courtine and the University Hospital of Lausanne (CHUV) lab of Prof. Jocelyne Bloch. NeuroRestore conceives, develops and applies medical therapies aimed to restore neurological functions. To this end, NeuroRestore integrates implantable neurotechnologies with innovative treatments developed through rigorous preclinical and clinical studies. By working with our network of vibrant high-tech start-ups and established medical technology companies, NeuroRestore is committed to validate our medical therapy concepts. The overarching goal of NeuroRestore is to see our medical therapies used every day in hospitals and rehabilitation clinics worldwide. Description: A therapy based on epidural electrical stimulation (EES) of the spinal cord can restore the ability to walk to people paralyzed by spinal cord injury. EES does this by recruiting sensory axons within dorsal spinal roots that enter the spinal cord between the vertebrae. Yet, clinically available electrode arrays used to deliver the EES were not designed to target individual spinal roots. Data-driven design of the electrode arrays has the potential to substantially improve the specificity of spinal EES and, therefore, dramatically improve the recovery of people with spinal cord injury. The efficacy of EES can be enhanced through computational algorithms capable of designing EES protocols that fully utilize the interaction between the electrode array and patient's anatomy. These two developments are critical for deployment of the EES-based therapy to clinics around the world to help millions of people suffering from spinal cord injury. We have created a computational pipeline capable of creating detailed computational models of spinal columns from CT, MRI and fMRI recordings. These hybrid models are composed of 3D finite element models (FEM) to characterize the electric current and potential in the spinal cord of individuals, and various abstractions of compartmental cable models and network models of spinal cord neuronal populations and their connections to calculate the effects of EES on the spinal networks and, in turn, the activation of muscles. This computational approach has the potential to optimize the efficacy of EES on a personalized basis, lead to novel superior electrode array designs, and further our understanding of the mechanisms by which spinal cord controls movement. The successful candidate will work to automatize our computational pipeline in order to make the described approaches useful in applied clinical practice. They will work on the development of efficient and robust computer vision algorithms to automatically segment medical imaging datasets. They will also further develop our computational pipeline to enable automatic definition of personalized EES stimulation protocols. Furthermore, they will implement a computational framework around our pipeline that can perform a large-scale and diverse sensitivity and uncertainty analysis. This framework will be critical to enhance the efficacy and explore possible novel applications of spinal cord EES. Prerequisites: - Master's Degree in Physics, Computer Science, Mathematics, Microengineering, Electrical Engineering or related - Proficiency in Python, Matlab and C++ - Experience with computer vision and / or other machine learning techniques - Good written and verbal skills in English Contact: Applications including a CV and a cover letter describing your background and interest should be sent to MachineLearningPhD.Courtine(a)gmail.com. Informal inquiries are welcome.

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Postdoc in machine learning at EPFL (Lausanne, Switzerland)
by Milekovic Tomislav Aug. 9, 2020

Aug. 9, 2020

Postdoc position in the lab of Prof. Gregoire Courtine at EPFL (Lausanne, Switzerland) Machine learning techniques to develop and enhance clinical treatments based on electrical stimulation of the spinal cord Location: The laboratory of Prof. Gregoire Courtine at the Swiss Federal Institute of Technology (EPFL) in Lausanne, Switzerland, is looking to fill a fully funded postdoc position. The qualified candidate will benefit from joining a very dynamic and multidisciplinary group working at the interface of computational neuroscience, neuroengineering, prosthetics and biology. EPFL provides state-of-the-art facilities and is one of the leading technical universities worldwide. Postdoc salaries at EPFL rank the highest in the world. Opportunity: The offered position will be based at the Defitech Center for interventional Neurotherapies (NeuroRestore) - a research and innovation center joining EPFL's lab of Prof. Gregoire Courtine and the University Hospital of Lausanne (CHUV) lab of Prof. Jocelyne Bloch. NeuroRestore conceives, develops and applies medical therapies aimed to restore neurological functions. To this end, NeuroRestore integrates implantable neurotechnologies with innovative treatments developed through rigorous preclinical and clinical studies. By working with our network of vibrant high-tech start-ups and established medical technology companies, NeuroRestore is committed to validate our medical therapy concepts. The overarching goal of NeuroRestore is to see our medical therapies used every day in hospitals and rehabilitation clinics worldwide. Description: Therapies based on epidural electrical stimulation (EES) of the spinal cord can restore the ability to walk to people paralyzed by spinal cord injury, and alleviate gait deficits of people with Parkinson's disease. EES does this by recruiting sensory axons within dorsal spinal roots that enter the spinal cord between the vertebrae to increase the activation of the spinal motor pools that, in turn, move the muscles. Yet, the efficacy of the EES-based therapies relies on synchronizing users' movement intentions with the spatiotemporal stimulation protocols that reliably and accurately generate paralyzed movements. Due to the large state space of all the stimulation parameters (location, amplitude, frequency, etc.) efficacy of the therapy depends on the fast and accurate initialization of the stimulation protocols. As the patients use the stimulation, small movements of the array, as well as changes in spine position due to users' posture can reduce the usability of the stimulation. Stimulation efficacy can be enhanced by dynamically adjusting the stimulation protocols to changes to the way how to users' spinal cord reacts to stimulation. Finally, the functional use of the stimulation largely depends on the accurate timing of stimulation delivery. Machine learning approaches that infer users' intentions based on behavioral, physiological or neural recordings can vastly improve the synchronization between intended and therapy-supported movements and, therefore, play a critical role in achieving functional recovery of patients. While the current medical devices mostly support block-based stimulation protocols that remain constant for hundreds of milliseconds, upcoming devices will enable changes of stimulation at a millisecond resolution, thus opening a new field for machine learning approaches that exploit these capabilities. The successful candidate will work to develop, implement and apply machine learning algorithms and approaches to enhance EES-based therapies. Specifically, he will: * Design the mapping procedures for the generation of transfer functions that relate the continuously-controlled stimulation to the evoked muscle activity. * Develop algorithms that automatically adjust these transfer functions as the interaction between patients and their EES-based therapy evolves. * Implement machine learning techniques that utilize users' behavioral, physiological and neural signals to continuously synchronize the delivery of stimulation with the users' movement intentions. * Lead the team that develops machine learning methods to initialize and adjust block-based EES protocols. * Assist and oversee the development and implementation of machine learning methods that use inference of discrete motor events to synchronize block-based EES protocols with the users' intentions. By integrating well-equipped and expertly staffed rodent, non-human primate and clinical research facilities, NeuroRestore provides an ideal substrate for rapidly developing, integrating and clinically validating cutting-edge machine learning concepts within medical therapies, with the capacity to push successfully proven concepts into the technology transition phase. The successful candidate will have access to these animal platforms and will work within the framework of multiple NeuroRestore clinical trials with people with spinal cord injury and Parkinson's disease. They will benefit from the possibility of validating their concepts in animal experiments and implementing them within the therapies being tested in the clinical trials. Prerequisites: * Doctoral degree (PhD) * Proficiency in Python, Matlab and C++ * Strong background in quantitative data analysis * Experience with applying multiple machine learning techniques to behavioral, physiological, biological and/or neural datasets * Good written and verbal skills in English Contact: Applications including a CV and a cover letter describing your background and interest should be sent to tomislav.milekovic(a)epfl.ch<mailto:tomislav.milekovic@epfl.ch>. Informal inquiries are welcome.

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Postdoc position in computational modelling at EPFL (Lausanne, Switzerland)
by Milekovic Tomislav Aug. 9, 2020

Aug. 9, 2020

Postdoc position in the lab of Prof. Gregoire Courtine at EPFL (Lausanne, Switzerland) Data-driven computational modelling to develop and enhance clinical treatments based on electrical stimulation of the spinal cord Location: The laboratory of Prof. Gregoire Courtine at the Swiss Federal Institute of Technology (EPFL) in Lausanne, Switzerland, is looking to fill a fully funded postdoc position. The qualified candidate will benefit from joining a very dynamic and multidisciplinary group working at the interface of computational neuroscience, neuroengineering, prosthetics and biology. EPFL provides state-of-the-art facilities and is one of the leading technical universities worldwide. Postdoc salaries at EPFL rank the highest in the world. Opportunity: The offered position will be based at the Defitech Center for interventional Neurotherapies (NeuroRestore) - a research and innovation center joining EPFL's lab of Prof. Gregoire Courtine and the University Hospital of Lausanne (CHUV) lab of Prof. Jocelyne Bloch. NeuroRestore conceives, develops and applies medical therapies aimed to restore neurological functions. To this end, NeuroRestore integrates implantable neurotechnologies with innovative treatments developed through rigorous preclinical and clinical studies. By working with our network of vibrant high-tech start-ups and established medical technology companies, NeuroRestore is committed to validate our medical therapy concepts. The overarching goal of NeuroRestore is to see our medical therapies used every day in hospitals and rehabilitation clinics worldwide. Description: Therapies based on epidural electrical stimulation (EES) of the spinal cord can restore the ability to walk to people paralyzed by spinal cord injury, and alleviate gait deficits of people with Parkinson's disease. EES does this by recruiting sensory axons within dorsal spinal roots that enter the spinal cord between the vertebrae. Yet, clinically available electrode arrays used to deliver the EES were not designed to target individual spinal roots. Data driven design of the electrode arrays has the potential to substantially improve the specificity of spinal EES and, therefore, dramatically improve the recovery of patients. Pre-operative planning and intra-operative assistance based on accurate models of the spine can de-risk the surgery needed to implant the electrode arrays and increase the efficacy of the EES-based therapies. The efficacy of EES can be further enhanced through computational algorithms capable of designing EES protocols that fully utilize the interaction between the electrode array and patient's anatomy. These developments are critical for deployment of the EES-based therapy to clinics around the world to help millions of people suffering from spinal cord injury and Parkinson's disease. We have created a computational pipeline capable of creating detailed computational models of individual persons' spinal columns from CT, MRI and fMRI scans. These hybrid models are composed of: * 3D finite element models (FEM) to characterize the electric current and potential in the spinal cord of individuals. * Compartmental cable models to characterize numerous axon pathways that distribute the information from the spinal cord to rest of the body. * Network models of spinal cord neuronal populations to calculate the effects of EES on the spinal networks and, in turn, the activation of muscles. This computational approach has the potential to optimize the efficacy of EES on a personalized basis, lead to novel superior electrode array designs, and further our understanding of the mechanisms by which spinal cord controls movement. The successful candidate will work to generate highly accurate models of individual human and animal model spines and apply those models to revolutionize the EES-based therapies. Specifically, he will: * Use spinal models to generate new spinal electrode array designs, develop procedures for pre-operative planning and intra-operative assistance, and create methods that determine stimulation protocols from the spinal models. * Lead the work to extend our lumbosacral spinal cord models to thoracic and cervical spinal regions. * Integrate data from ever-more accurate invasive and non-invasive medical imagining and physiology techniques to enhance the accuracy of spinal models. * Coordinate integration of new findings on spinal neuronal populations, spinal networks and spinal pathways into our spinal models. * Assist and oversee the development of tools to automatize the process of spinal model generation. By integrating well-equipped and expertly staffed rodent, non-human primate and clinical research facilities, NeuroRestore provides an ideal substrate for rapidly developing, integrating and clinically validating cutting-edge computational modeling concepts that support medical therapies, with the capacity to push successfully proven concepts into the technology transition phase. The successful candidate will have access to these animal platforms and will work within the framework of multiple NeuroRestore clinical trials with people with spinal cord injury and Parkinson's disease. They will benefit from the possibility of validating their concepts in animal experiments and implementing them within the therapies being tested in the clinical trials. Prerequisites: * Doctoral degree (PhD) * Proficiency in Python, Matlab and C++ * Experience with finite element models, compartmental cable models and neurobiomechanical models * Experience in NEURON and/or NEST * Experience in OpenSim, Mujoco or Webots * Good written and verbal skills in English Contact: Applications including a CV and a cover letter describing your background and interest should be sent to tomislav.milekovic(a)epfl.ch<mailto:tomislav.milekovic@epfl.ch>. Informal inquiries are welcome.

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Post-doctoral scientist position at the Steinmetz Lab, University of Washington, Seattle
by Nick Steinmetz Aug. 6, 2020

Aug. 6, 2020

The Steinmetz Lab at the University of Washington in Seattle ( www.steinmetzlab.net) is seeking applications for a position as a post-doctoral scientist. The scientist will work on data analysis and modeling in order to advance our large-scale electrophysiology technologies and our understanding of distributed computation across the brain. The primary focus of the position is the ‘Neuropixels Ultra’ project, in which we are developing novel electrophysiological technologies in collaboration with colleagues at the Allen Institute for Brain Science and with Johns Hopkins University. In addition to work on that specific project, the scientist will have access to cutting-edge large-scale datasets that combine behavior, electrophysiology, imaging, and optogenetics, and will have the ability to work creatively on questions of their own choosing, including helping to guide novel experimental data collection as necessary. The position is funded for 3 years by an NIH BRAIN Initiative grant, and is eligible to start immediately. It is expected that the scientist will eventually be based in Seattle, but a remote start is negotiable considering health concerns related to the ongoing global pandemic. The successful candidate is expected to have a Ph.D. in neuroscience or in relevant quantitative fields such as physics, computer science, statistics, or mathematics, and is expected to have a strong background and interest in data analysis methods in neuroscience, including such approaches as signal processing, linear algebra, and dynamical systems. We are located at the University of Washington, and have close collaborations with the Computational Neuroscience Center, the Swartz Center for Theoretical Neuroscience, the UW Institute for Neuroengineering, and the Allen Institute for Brain Science, which together create a lively community of computationally-minded neuroscientists on and near campus. The Steinmetz Lab is committed to making neuroscience a more open and inclusive field, so we strongly encourage applications from individuals with non-traditional backgrounds or from underrepresented groups. To apply, please send a CV and a brief statement of your background and interest in the position to Nick Steinmetz at nick.steinmetz(a)gmail.com. Informal inquiries are welcome - please get in touch if you would like more information! We aim to start this position as soon as possible so please be in touch by Friday Aug 21.

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Free online workshop on spiking neural networks as universal function approximators, Aug 31-Sep 1
by Dan Goodman Aug. 6, 2020

Aug. 6, 2020

We are holding a free, online workshop on new approaches to training spiking neural networks. Details and registration at: https://neural-reckoning.github.io/snn_workshop_2020/ The last years have seen many exciting new developments to train spiking neural networks to perform complex information processing. This online workshop brings together researchers in the field to present their work and discuss ways of translating these findings into a better understanding of neural circuits. Topics include artificial and biologically plausible learning algorithms and the dissection of trained spiking circuits toward understanding neural processing. Speakers: * *Sander Bohte* (CWI) * *Iulia M. Comsa* (Google) * *Franz Scherr* (TUG) * *Emre Neftci* (UC Irvine) * *Timothee Masquelier* (CNRS Toulouse) * *Claudia Clopath* (Imperial College) * *Richard Naud* (U Ottawa) * *Julian Goeltz* (Uni Bern) Please pass this message on to anyone you think would be interested. Many thanks, Dan Goodman and Friedemann Zenke

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Postdoctoral position in neuroscience model curation / reproducible research
by Andrew Davison Aug. 5, 2020

Aug. 5, 2020

A position in neuroscience model curation and verification is available within the Neuroinformatics research group of the Paris-Saclay Institute of Neuroscience, as part of the Human Brain Project. The successful candidate will be responsible for verifying the reproducibility of models produced by the Human Brain Project and/or published through the EBRAINS research infrastructure. This will involve working with scientists from many institutions to ensure their code is usable by others, and that it reliably reproduces the results shown in associated publications. It is expected that the candidate will develop workflows to automate this verification process as much as possible. Applicants should have a PhD in neuroscience, computer science, library/information science, or a closely related discipline, preferably with experience of computational modelling. Experience of simulation tools often used in computational neuroscience, such as NEURON, NEST or Brian, would be of particular benefit; knowledge of computer programming (in Python, C++, MATLAB or other) is essential. Knowledge of French would be helpful but is not required, as English is the working language of the project. The Paris-Saclay Institute of Neuroscience (https://neuropsi.cnrs.fr/en/institute-home/) is a research unit of the CNRS and the Université Paris-Saclay, located in Gif sur Yvette, about 40 minutes from central Paris. The Neuroinformatics research group (https://neuropsi.cnrs.fr/en/icn-home/andrew-davison/ <https://neuropsi.cnrs.fr/en/icn-home/andrew-davison/>) develops novel informatics tools and approaches for neuroscience data sharing, modelling and simulation, and for brain-inspired computing. This post is funded by the Human Brain Project, an EU Flagship initiative in which over 100 partners work together to build a completely new information computing technology infrastructure for neuroscience and for brain-related research in medicine and computing. To apply, visit https://emploi.cnrs.fr/Offres/CDD/UMR9197-ANDDAV-005/Default.aspx <https://emploi.cnrs.fr/Offres/CDD/UMR9197-ANDDAV-005/Default.aspx> Informal inquiries to andrew.davison(a)cnrs.fr <mailto:andrew.davison@cnrs.fr> are welcome. Application deadline 17th August 2020

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Postdoctoral, predoctoral, and data scientist positions: causal inference
by Jan Drugowitsch Aug. 5, 2020

Aug. 5, 2020

How do our brains interpret sensory inputs to determine how we move through the world? How do the objects we perceive in the environment shape these interpretations? And what happens when these objects are themselves moving? We will address these questions in a multi-institution project that examines neural and computation mechanisms of causal inference in the context of interactions between perception of object motion, self-motion, and depth. We are looking for talented and creative scientists to join our effort. We are offering multiple positions for postdoctoral fellows, graduate research assistants, and a data scientist as part of a BRAIN Initiative U19 project focused on the neural mechanisms of causal inference. This multi-institution project involves experimental and computational/theoretical laboratories at the University of Rochester (Drs. Greg DeAngelis and Ralf Haefner), Harvard Medical School (Dr. Jan Drugowitsch), New York University (Dr. Dora Angelaki), Baylor College of Medicine / Rice University (Dr. Xaq Pitkow), and the University of Washington (Dr. Greg Horwitz). The project is highly collaborative and interactive, involving high-density electrophysiological recordings in both macaque monkeys and mice, optogenetic manipulations in monkeys, development of novel dynamical theoretical frameworks, application of high-dimensional neural analyses, and establishment of a data analysis and storage platform across laboratories. For the theoretical/computational efforts, candidates are expected to have a background in a quantitative field like computational neuroscience, machine learning, reinforcement learning, statistics, physics, etc.. For the experimental efforts, candidates are expected to have a background in neuroscience, experimental psychology, biomedical engineering, or a related field, and previous research experience in systems neuroscience is highly beneficial. Successful candidates will work primarily at one of the participating institutions but will collaborate broadly with team members across institutions. Candidates should submit their CV, a statement of research interests, and the names and contact information for three references. Please consult https://www.indeed.com/job/postdoctoral-predoctoral-and-data-scientist-posi… for further details, and for how to apply.

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Postdoctoral positions in computational neuroscience, sleep, and developmental neurophysiology
by Blumberg, Mark S Aug. 4, 2020

Aug. 4, 2020

We are seeking to fill multiple positions for highly skilled and motivated postdoctoral scholars. Successful applicants will learn to perform experiments in neurophysiology and sleep, as well as develop computational models based on years of spike and LFP data collected in infant rats and, more recently, human infants. We have developed state-of-the-art multisite recording methods to detect neural activity in cortex, hippocampus, thalamus, cerebellum, and brainstem in developing rats and relate that activity to changes in sleep-wake states and limb movements (captured using high-speed video and tracked using DeepLabCut). Unique opportunities abound for analyzing and modeling these complex datasets to reveal functional changes in neural activity across the first several postnatal weeks. Among other things, we are investigating the integration of corollary discharge and reafferent signals, the role of state-dependent neuromodulation, and the contributions of neural oscillations to the emergence of functionally connected brain regions. Please visit the lab’s homepage<https://psychology.uiowa.edu/blumberg-lab> and read our recent papers<https://psychology.uiowa.edu/blumberg-lab/articles> to gain a better sense of the kinds of questions we ask and the methods we use to answer them. You can learn more about the PI, Mark Blumberg, here<https://psychology.uiowa.edu/sites/psychology.uiowa.edu/files/groups/blumbe…> and here<https://psychology.uiowa.edu/sites/psychology.uiowa.edu/files/groups/blumbe…>. The laboratory is located in the Department of Psychological and Brain Sciences<https://psychology.uiowa.edu/> at the University of Iowa<https://uiowa.edu/>, a leading public university. The university is located in Iowa City, a midsize community with a high quality of life. The department is experiencing a period of enhanced growth and investment, including completion of a new building<https://psychology.uiowa.edu/new-home-department-psychological-and-brain-sc…>. In addition, the University of Iowa is home to a large and vibrant neuroscience community, highlighted by the Iowa Neuroscience Institute<https://medicine.uiowa.edu/iowaneuroscience/> that brings together over 100 neuroscientists across 26 departments. In addition to research opportunities, successful applicants will have opportunities to teach courses, mentor graduate and undergraduate students, write grants, and engage in activities to enhance professional development and prepare for an academic career. Salary is negotiable, but is expected to be above NIH's minimum guidelines for postdocs. Requirements: A PhD with experience in computational and/or behavioral neuroscience. Experience with MATLAB (or other programming languages) is required. Please send a letter of interest, curriculum vitae, and selected publications to Mark Blumberg at mark-blumberg(a)uiowa.edu<mailto:mark-blumberg@uiowa.edu>. _________________________________ Mark S. Blumberg, Ph.D. F. Wendell Miller Professor Department Chair Psychological & Brain Sciences Iowa Neuroscience Institute The University of Iowa _________________________________

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Submit Now - Call for Research Projects | Bitbrain
by Eduardo López-Larraz Aug. 4, 2020

Aug. 4, 2020

Call for Research Projects Bitbrain grants up to 150K€ of equipment for Research Projects in the areas of human behavior and brain-computer interfaces. Aim of the Call This year has been unexpectedly complicated for all of us. We have had an ongoing threat to public health with a strong impact on economic activity in every country and organization. Scientific endeavors have been delayed in most research fields, and many research conferences and symposiums have been delayed or canceled. The aim of this call is to catalyze and mobilize research in human behavior and brain-computer interfaces during this difficult time, by supporting outstanding research projects for 2 years of duration starting in 2021. This is our way of giving back to the scientific community and helping research projects start-up in the wake of COVID 19. Bitbrain's mission is to boost real-world research and real-life applications that enhance people's lives. For this reason, we particularly welcome project proposals from academia or research institutions that are exploring neuroscience research in real-world settings. The deadline for submissions is September 21st, 2020. More info here: https://www.bitbrain.com/call-for-projects-2020 <https://urldefense.com/v3/__https://www.bitbrain.com/call-for-projects-2020…> The Awards This initiative awards projects with up to a total of 150K€ in Bitbrain equipment plus software licenses. Bitbrain systems are specifically designed to facilitate research in real-world settings and include high-tech EEG brain sensing devices and 35+ complementary monitoring technologies, as well as human behavior research software solutions for synchronized multimodal data acquisition and analysis. Call topics 1. Topic 1: Human Behavior Research: We are looking for projects that expand the understanding of human behavior using multimodal approaches, preferably in ecological and natural conditions. The research includes, but is not limited to, cognitive sciences, clinical research, education, developmental psychology, human performance, UX or human factors, neuroeconomics, hyperscanning, neuroaesthetics, etc. Awards: According to the research needs of the project, the award may include the following: 1) Hardware: dry/semi-dry EEG systems in combination with a wide range of biosensors (GSR, BVP, ExG, etc) specifically developed to carry out real-world research, while favoring signal quality, usability, set up time, and user comfort. 2) Software: SDK for real-time I/O and third-party data processing (LSL, Matlab, Python, BCI200, etc); SennsLab software for synchronized data collection of 35+ types of biosensors and other research modalities including eye-tracking, cameras, microphones, etc, and other 3rd party options such as E-prime; SennsMetrics software for computation and data analysis of behavioral metrics. 1. Topic 2: Brain-Computer Interfaces (BCI): We are looking for projects that expand the introduction or usage of brain-computer interfaces in ecological and natural conditions. Research project proposals should focus on the application of brain-computer interfaces in real-world scenarios, in areas such as immersive environments, neurorehabilitation, neuroadaptive technologies, hyperscanning, neuroprosthetics, etc. Awards: According to the research needs of the project, the award may include the following: 1) Hardware: Mobile EEG systems for brain-computer interfaces including dry-EEG devices and semi-dry EEG systems (8, 16, 32 and 64ch), with a very quick and easy setup and comfortable interface. 2) Software: programming tools with great compatibility with real-time I/O and third-party data processing (LSL, Matlab, Python, BCI2000, OpenVibe, etc). Jury 1. Alan Kingstone, Ph.D. <https://psych.ubc.ca/profile/alan-kingstone/>, Professor, Department of Psychology, University of British Columbia. Canada. 2. Ander Ramos, Ph.D. <https://www.ramoslab.org/>, Head of the Neurorehabilitation Lab. University of Tübingen. Germany. 3. Dima Amso, Ph.D. <https://www.brown.edu/academics/cognitive-linguistic-psychological-sciences…>, Professor, Department of Psychology at Columbia University. USA. 4. Gernot Müller-Putz, Ph.D. <https://www.tugraz.at/institutes/ine/people/gernot-mueller-putz/>, Professor and Head of the Institute of Neural Engineering. Graz University of Technology. Austria. 5. Marco Congedo, Ph.D. <https://www.gipsa-lab.grenoble-inp.fr/page_pro.php?vid=518>, Charge de Research (CNRS), France. 6. Tad Brunye, Ph.D <https://ase.tufts.edu/psychology/spacelab/members.htm>., Visiting Associate Professor, Department of Psychology, Tufts University; Senior Research Psychologist, Army Natick Soldier Research, Development, and Engineering Center, USA. 7. Tiago Falk, Ph.D. <http://musaelab.ca/team-view/prof-tiago-h-falk/>, Associate Professor and Multimedia/Multimodal Signal Analysis and Enhancement (MuSAE) Laboratory. University of Toronto. Canada. Important Dates - Submission of applications: 21st September - Communication of the awards: 6th October - Contracts: 12th October - Equipment delivering: 20th December - Kick-off Meetings: 11th January More info here: https://www.bitbrain.com/call-for-projects-2020 <https://urldefense.com/v3/__https://www.bitbrain.com/call-for-projects-2020…>

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Bernstein Conference 2020 – registration now open
by a.dorrn＠fz-juelich.de Aug. 4, 2020

Aug. 4, 2020

Each year the Bernstein Network invites the international computational neuroscience community to the annual Bernstein Conference for intensive scientific exchange. It has established itself as one of the most renown conferences worldwide in this field, attracting students, postdocs and PIs from around the world to meet and discuss new scientific discoveries. This year’s Bernstein Conference will take place September 29 - October 1, 2020 and will be held entirely online for the first time. It will be followed by the online Bernstein PhD Symposium on October 2, 2020. www.bernstein-conference.de<https://bit.ly/BC_online> ____ NEWS · Registration is now open: bit.ly/BC20_Registration<https://bit.ly/BC20_Registration> · Participation will be free of charge · Abstract submission deadline is approaching on August 21 Please find more information here: bit.ly/BC20abstracts<https://bit.ly/BC20abstracts> · Program for online Bernstein PhD symposium is now online: bit.ly/bc20_phd<https://bit.ly/bc20_phd> ____ INVITED SPEAKERS William Bialek (Princeton University, USA) Michael Brecht (Humboldt Universität zu Berlin, Germany) Laura Busse (LMU Munich, Germany) Megan Carey (Champalimaud Center for the Unknown, Lisbon, Portugal) Rosa Cossart (Institut de neurobiologie de la méditerrané, Marseille, France) Ann Hermundstad (Janelia Research Campus, Ashburn, USA) Roozbeh Kiani (New York University, New York City, USA) Vanessa Ruta (The Rockefeller University, New York City, USA) David Sussillo (Google AI, Mountain View, USA) Srdjan Ostojic (L'école normale supérieure, Paris, France) Fred Wolf (Max-Planck Institute for Dynamics and Self-Organization, Göttingen, Germany) ____ CONFERENCE COMMITTEE Udo Ernst (Conference Chair) Elad Schneidmann (Program Chair) Julijana Gjiorgjieva (Program Vice Chair) Tim Vogels (Workshop Chair) Marion Silies (Workshop Vice Chair) Henning Sprekeler (Conference Host) Danielle Bassett, Matthew Botvinick, Peter Dayan, Alain Destexhe, Tim Gollisch, Stephanie Palmer, Nathalie Rochefort, Nicole Rust, Gasper Tkacik ____ For any further questions, please contact: bernstein.conference(a)fz-juelich.de ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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3- or 4-yearpostdoc position available for analysis of large neural data
by Benjamin Dunn Aug. 3, 2020

Aug. 3, 2020

Funded by the Norwegian Research Council, the available position is part of a collaborative project on personalized rehabilitation of stroke patients evaluated with multimodal quantitative tools (PROTEQT). The selected candidate can start as early as October 1st, 2020. She or he will be part of a research group focused on neural data science at the Department of Mathematics at NTNU. We have a wonderful group and surrounding community. Norway is lovely (especially now). This position is for the development of methods to analyze neural data -- in particular, to compare across subjects and describe changes as the underlying network develops (e.g. during recovery from a stroke). The main datasets are multimodal MRI, to be analyzed in collaboration with another postdoc and PhD student. There is also other data around and plenty of room for theoretical work. Email me at benjamin.dunn(a)ntnu.no if you have any questions. Please apply here: https://jobbnorge.no/en/available-jobs/job/190466/postdoctoral-fellowship-i… Note the deadline: August 20th Here are some publications: https://scholar.google.com/citations?user=hAjFjXkAAAAJ&hl=en And an example of something we are working on: https://youtu.be/Hlzqvde3h0M Thanks, Ben

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postdoc position in systems neuroscience: translational project to study sleep and memory
by Carmen Varela Aug. 3, 2020

Aug. 3, 2020

*We are opening a postdoctoral position to investigate non-invasive approaches to enhance sleep oscillations and memory function in rats. *This translational project is part of a collaboration between the laboratories of Dr. Carmen Varela (Psychology Department, Florida Atlantic University, FAU; https://www.varelalab.org/) and Dr. Dara Manoach (Massachusetts General Hospital-Harvard Medical School). The project will be conducted at FAU and it will involve frequent interaction with collaborators in Boston. The postdoc will gain expertise in systems and translational neuroscience using electrophysiology (cell ensemble and LFP recording with high-density probes) and behavior in rodents, as well as expertise on the mechanisms underlying normal and disrupted sleep-dependent memory consolidation processes and the use of non-invasive technologies to regulate them. *Requirements:* PhD with experience in electrophysiology and rodent models; outstanding interpersonal skills and motivation to work in a collaborative environment. Experience with MATLAB (or other programming languages) preferred. Candidates selected for an interview will be asked to provide contact information for three references. *Anticipated start day in January 2021. * One year with possibility of extension. Interested applicants, please submit your curriculum to Carmen Varela: varelac(a)fau.edu FAU is an equal opportunity/affirmative action institution and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veterans’ status or any other characteristic protected by law. Best, *Carmen Varela, Ph.D.* Assistant Professor Psychology Department Florida Atlantic University MC-19, room 106 Jupiter, FL 33458

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DeepMath 2020: call for abstracts
by Kamesh Krishnamurthy July 30, 2020

July 30, 2020

Dear all, We are now accepting abstract submissions to the 2020 Conference on the mathematical theory of deep neural networks (DeepMath). DeepMath is a highly interdisciplinary conference focused on understand fundamental theory driving the empirical success of Deep Learning. We are excited for this year's diverse set of invited speakers (see https://deepmath-conference.com for more information) and invite additional contributions from the community. Due to ongoing concerns about Covid-19, this year’s DeepMath conference will be conducted virtually. We are presently working on finalizing an online format that will seek to capture the small, community-focused experience of past DeepMath events. Important updates related to submission and registration are included below: == Submissions == We are still accepting submissions for virtual “posters” consisting of a pre-recorded talk and Q&A session. Similarly to last year, a selected number of top posters will be invited to present their work live as contributed talks. == Registration == Participation in the conference will require registration costing a nominal fee. We are working to keep costs as low as we can given the online nature of the event. As with last year, all talks will be live-streamed for free. More information on submissions can be found at the DeepMath website at https://deepmath-conference.com/submissions Warmest regards, The DeepMath Organizing Committee

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Postdoctoral position to study the neural circuit of social behavior
by Hong, Weizhe July 30, 2020

July 30, 2020

The Hong Lab at UCLA (hong-lab.com) is looking for a new postdoc to study the neural circuit of social behavior in mice. We are particularly interested in candidates with expertise in systems and/or computational neuroscience. Social interactions between individuals and among groups are a hallmark of human society as we know it and are critical to the physical and mental health of a wide variety of species including humans. Impairment of social function is a prominent feature of many neuropsychiatric disorders such as autism spectrum disorders and schizophrenia. Nonetheless, many fundamental questions regarding the neural mechanisms underlying social behavior remain unanswered. The central goal of Weizhe Hong’s laboratory is to study general principles of how social behavior is regulated in the brain. We take a multi-disciplinary approach and uses a variety of experimental and computational technologies across molecular, circuit, and behavioral levels. We are interested in how neural dynamics regulates social behavioral decisions within a single brain as well as how emergent inter-brain neural properties arise from social interactions between individuals. For more information, please visit hong-lab.com. Recent publications: 1. Kingsbury L, Hong W. (2020) A multi-brain framework for social interaction. Trends in Neurosciences. doi: 10.1016/j.tins.2020.06.008. (Review) 2. Kingsbury L, Huang S, Raam T, Ye LS, Wei D, Hu R, Ye L, Hong W. (2020) Cortical representations of conspecific sex shape social behavior. Neuron. doi: 10.1016/j.neuron.2020.06.020. 3. Chen PB, Hu RK, Wu YE, Pan L, Huang S, Micevych PE, Hong W. (2019) Sexually dimorphic control of parenting behavior by the medial amygdala. Cell. 176, 1206-1221. 4. Kingsbury L, Huang S, Wang J, Gu K, Golshani P, Wu YE, Hong W. (2019) Correlated neural activity and encoding of behavior across brains of socially interacting animals. Cell. 178, 429-446. 5. Chen P, Hong W. (2018) Neural circuit mechanisms of social behavior. Neuron. 98, 16-30. (Review) 6. Wu YE, Pan L, Zuo Y, Li X, Hong W. (2017) Detecting activated cell populations using single-cell RNA-seq. Neuron. 96, 313-329. -- Weizhe Hong, Ph.D. Associate Professor Department of Biological Chemistry Department of Neurobiology David Geffen School of Medicine University of California, Los Angeles Graduate Program Affiliations: Neuroscience PhD Program at UCLA Bioengineering PhD Program at UCLA Bioinformatics PhD Program at UCLA Molecular, Cellular, and Integrative Physiology PhD Program at UCLA ________________________________ UCLA HEALTH SCIENCES IMPORTANT WARNING: This email (and any attachments) is only intended for the use of the person or entity to which it is addressed, and may contain information that is privileged and confidential. You, the recipient, are obligated to maintain it in a safe, secure and confidential manner. Unauthorized redisclosure or failure to maintain confidentiality may subject you to federal and state penalties. If you are not the intended recipient, please immediately notify us by return email, and delete this message from your computer.

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Online tutorial on Brian simulator: Aug 7th, 2-6pm BST
by Dan Goodman July 30, 2020

July 30, 2020

The Brian team will be running an online tutorial for Brian on August 7th, 2-6pm BST (=UTC+1). Please do come along or get your students/postdocs to come along. Registration is required but free (to prevent zoombombing), at the link below: https://www.eventbrite.co.uk/e/brian-online-tutorial-tickets-115336320038 You'll get an email with a link to an 'event details' page with the Zoom URL. Please don't share this online to help prevent zoombombing. This is an experiment for us, if it's successful we might turn it into a regular thing. For the moment, the content of the tutorial is not decided. Have your say here: https://twitter.com/neuralreckoning/status/1288768229591207938 And, if you're an experienced Brian user and would like to volunteer to help - get in touch! Thanks, Dan

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PhD position in network neuroscience at University of Sussex
by Luc Berthouze July 29, 2020

July 29, 2020

Applications are invited for a fully-funded PhD scholarship to undertake research in network neuroscience at the University of Sussex. A number of conditions, such as Parkinson’s Disease, are referred to as ‘oscillopathies’ because there is evidence that some of their major symptoms are underpinned by pathological synchronisation of neurons in key networks. A promising form of treatment is that of online control of deep brain stimulation based on computational processing of brain signals. Therefore, new mathematical insights about how to detect and efficiently disrupt pathological processes can be rapidly translated to patient benefit. Using models of oscillations on networks, this project will seek to investigate the conditions (either on the oscillators themselves, or the connectivity, or factors that may frustrate the interplay between dynamics on and dynamics of the network) under which pathological oscillations in one small area of the brain can intermittently or otherwise ‘infect’ the wider network of the brain causing the pathological symptoms. This project will involve an active collaboration with Dr Simon Farmer at University College London (UCL). This 3-year studentship includes student fees and a tax-free stipend starting at £15,285 per annum. It also comes with a generous Research Training Support Grant. Start date is flexible. Eligibility All nationalities are eligible to apply for this studentship. You should have a first-class honour degree or equivalent, or an MSc degree (preferably), in Computer Science, Mathematics or Physics (or relevant disciplines). You will have (and enjoy using) strong analytical skills as well as excellent programming skills in at least one of C++, Python, Matlab. Applicants interested in the post, seeking further information or feedback on their suitability are encouraged to contact me. All applications must be made via http://www.sussex.ac.uk/study/phd/apply where you will find details of entry requirements. Please clearly state on your application form that you are applying for 'Dynamics on/of networks and oscillopathies'. Luc Berthouze Professor of Complex Systems University of Sussex

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2020 Big Data Neuroscience *free* Workshop Invitation
by Franco Pestilli July 29, 2020

July 29, 2020

Dear All. We are organizing the 2020 Big Data Neuroscience workshop as an online event. It will be a 1-day event with 4 keynote speakers, software demos, and a series of lightning talks. http://neurosciencenetwork.org/ACNN_Workshop_2020.html We would like to invite you to register for the FREE event and consider signing up for a lighting talk. You are welcome to share this announcement broadly. Best regards, Franco *FRANCO PESTILLI*, *Ph.D.* | *Associate Professor* he/him | pestilli(a)utexas.edu | web <https://liberalarts.utexas.edu/psychology/faculty/fp4834> | github <https://github.com/francopestilli> | brainlife.io

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postdoc position in model-based fMRI at Harvard (Gershman/Buckner labs)
by Sam Gershman July 29, 2020

July 29, 2020

The Gershman (gershmanlab.webfactional.com) and Buckner ( https://cnl.rc.fas.harvard.edu/) labs at Harvard University are seeking a postdoctoral fellow to work on a longitudinal functional MRI project. The aim of this project is to understand how computationally defined phenotypes change across time, and how these changes map onto dynamic functional networks in the human brain. Candidates must have a strong background in fMRI research and statistical analysis. Experience with computational cognitive modeling is preferred but not required. The start date for this position is on or around February 1, 2021, but this can be flexibly adjusted as needed. The position is fully funded for 2 years, with a possible extension to a 3rd year contingent on funding. We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law. Interested applicants should contact Sam Gershman (gershman(a)fas.harvard.edu) along with a CV and list of references.

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