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Fwd: Faculty position at CHAIN: Assistant Professor or Lecturer

by Hideaki Shimazaki

Dear colleagues, Apologies for multiple posting. There was an error in the deadline for this faculty search in the previously posted email. The deadline for applications is June 30 (not June 8). Sincerely, Hideaki --- Hideaki Shimazaki, Ph.D https://www.neuralengine.org ---------- Forwarded message --------- From: Hideaki Shimazaki <shimazaki(a)chain.hokudai.ac.jp> Date: Fri, May 15, 2020 at 9:57 PM Subject: Faculty position at CHAIN: Assistant Professor or Lecturer To: <comp-neuro(a)neuroinformatics.be> Dear colleagues, Our newly established Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN) at Hokkaido University in Japan invites applications for a faculty position at the Assistant Professor or Lecturer level. The full description and details are attached below. See also: https://jrecin.jst.go.jp/seek/SeekJorDetail?fn=3&ln=1&id=D120050453&ln_jor=1 https://www.chain.hokudai.ac.jp/?lang=en The deadline for applications is 8 June 2020 (JST). The deadline for applications is 30 June 2020 (JST). All the best, Hideaki --- Hideaki Shimazaki, Ph.D https://www.neuralengine.org Position Open: Assistant Professor or Specially Appointed Lecturer, Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN), Hokkaido University Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN), Hokkaido University, in Hokkaido, Japan invites applications for a 3.5 year research and teaching position with an anticipated start date of September 1st, 2020. The successful applicant will be appointed as a faculty member at the rank of Specially Appointed Assistant Professor or Lecturer in CHAIN. Women and members of other underrepresented groups are particularly encouraged to apply. CHAIN is a research and education center for interdisciplinary studies in the humanities, social sciences, neuroscience, and artificial intelligence. It aims to open up new directions of research into the nature of human existence by fostering interaction and collaboration between humanities and the social sciences, including philosophy, ethics, psychology (cognitive and social), law, and economics, and the natural sciences, such as neuroscience, AI, and cognitive science. In particular, it focuses on connecting philosophical ideas with methods and insights of mathematical and empirical sciences. A new interdisciplinary graduate program of CHAIN starts in July 2020. Qualifications The ideal applicant will have an independent research project that will strengthen and complement existing interdisciplinary research in CHAIN. They are expected to demonstrate the following qualities and characteristics: 1. A PhD by the time of the appointment in one (or more) of the following area(s): philosophy, ethics, psychology, cognitive science, neuroscience, AI, information science, or robotics. 1. Outstanding publication records and/or demonstrable potential to publish in highly esteemed publication outlets. 1. Strong motivation to fulfill research, teaching, and administrative duties as a faculty member in CHAIN. 1. Enthusiasm and competence for delivering postgraduate and undergraduate courses on topics pertinent to CHAIN’s research and education goals. 1. A demonstrated ability and strong interest to develop and engage in interdisciplinary research projects in collaboration with existing members of the institution. Application materials Submit the following materials, compiled in a single ZIP file, via email at jobs [at]chain.hokudai.ac.jp to complete your application: 1. Curriculum Vitae* 2. Summary of past research accomplishments (1-2 pages) 3. Three most important publications relevant to this position. 4. Brief statement of research and teaching interests (1-2 pages) 5. Two references (Names and contact details) Use common fonts such as Times New Roman in black and size 12 points. Submit each publication in a separate PDF file. Compile all the rest (1, 2, 4, and 5) in a single PDF file. This makes four PDF files in total, which must then be compiled in a single ZIP file. Submission is due Monday, 8 June, 2020 (JST) *Tuesday 3 June, 2020 (JST)*. The subject line of the email must read “Application (Lecturer/Assistant Professor).” You will receive a confirmation email shortly after making a submission. Please contact us immediately if you did not receive one within 3 business days. Personal information obtained through these materials will only be used within this selection process. *Applicants who have been employed by Hokkaido University after April 1, 2014 (in any position, including Part-time Lecturer, Teaching Assistant, Teaching Fellow, Research Assistant and Short-term Support Assistant, etc.) should provide full details of their employment history in the CV. Appointment terms This is a full-time research and teaching position with an anticipated start date of September 1st, 2020. The salary will be paid under the annual-salary scheme and the discretionary labor system. The annual salary is determined in accordance with the internal regulations of Hokkaido University. Upon employment, one will be enrolled in the Ministry of Education, Culture, Sports, Science and Technology Mutual Aid Association, Employees Pension, Workers’ Accident Compensation Insurance and Employment Insurance. A one month probationary period applies. Questions about the position should be addressed to the chair of the search committee, Shigeru Taguchi (inquiry[at]chain.hokudai.ac.jp). Further information Website: www.chain.hokudai.ac.jp/?lang=en Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN) Hokkaido University Kita 12 Nishi 7, Kita-ku, Sapporo Hokkaido 060-0812 Japan Application submission: jobs [at] chain.hokudai.ac.jp Inquiries: : inquiry [at] chain.hokudai.ac.jp

May 24, 2020

Publication of the NeurIPS2019 Reproducibility Challenge reports

by Nicolas P. Rougier

Dear all, The accepted reports for the NeurIPS2019 Reproducibility challenge have just been published at https://rescience.github.io/read (volume 6, issue 2). All articles are open access with open code, data and reviews. Nicolas Rougier ReScience C Editor-in-chief

May 22, 2020

Community review of two new standards now open

by Helena Ledmyr

INCF has two new community standards up for public review, and we are now soliciting input from the user community. The standards are the Neuroscience Information Exchange (NIX) and the Neuroimaging Data Model (NIDM)-Results. More information is available here: https://www.incf.org/comment-on-these-sbps *The mission of the INCF is to develop, evaluate, and endorse standards and best practices that embrace the principles of Open, FAIR, and Citable neuroscience. INCF also provides training on how standards and best practices facilitate reproducibility and enables the publishing of the entirety of research output, including data and code.* All the best Helena ----------------------------- Helena Ledmyr, PhD *Director* *Development and Communications* International Neuroinformatics Coordinating Facility Secretariat Karolinska Institutet. Nobels väg 15A, SE-171 77 Stockholm. Sweden Email: helena.ledmyr(a)incf.org Phone: +46 8 524 870 35 incf.org neuroinformatics.incf.org

May 22, 2020

Call for papers: Neuroinformatics special issue "Building the NeuroCommons"

by Helena Ledmyr

Neuroinformatics is currently soliciting submissions for a special issue called "Building the NeuroCommons - research and commentary on how neuroscience is becoming open and FAIR". Submissions due *July 31 2020*. As neuroscience increasingly defines and adopts FAIR, the act of publishing in neuroscience will not only serve to communicate new research but drive the population of a robust, more data- and resource-driven ecosystem - the NeuroCommons - on which to build further findings. This special, open-access, issue of Neuroinformatics is dedicated to building the NeuroCommons and will include articles that embody the principles of open and FAIR neuroscience: - FAIRification of neuroscience data, tools and other research objects: What does it take to move neuroscience closer to the ideal of FAIR? - Using public data to drive discovery science - Research infrastructure for neuroscience and how it supports open and FAIR neuroscience - Standards-based neuroscience. When and where have standards been effective? What have we learned about creating standards and gaining adoption? Where are they lacking? - Perspectives and commentary on the concept of the NeuroCommons, e.g., what will it take for neuroscience to become a data-driven discipline based on pools of open research data? What are challenges and opportunities? Where have there been successes? More information and submission at https://www.springer.com/journal/12021/updates/17978796 All the best Helena ----------------------------- Helena Ledmyr, PhD *Director* *Development and Communications* International Neuroinformatics Coordinating Facility Secretariat Karolinska Institutet. Nobels väg 15A, SE-171 77 Stockholm. Sweden Email: helena.ledmyr(a)incf.org Phone: +46 8 524 870 35 incf.org neuroinformatics.incf.org

May 22, 2020

Imperial College MRes in Neurotechnology

by Kozlov, Andriy

Imperial College MRes in Neurotechnology Neurotechnology is the use of insights and tools from mathematics, physics, chemistry, biology and engineering to investigate neural function and treat dysfunction. Brain-related illnesses affect more than two billion people worldwide, and the numbers are growing. Reducing this burden is a major challenge for society. The MRes Neurotechnology<http://www.imperial.ac.uk/bioengineering/study/postgraduate-research/mres-n…> is a one-year full-time programme which will provide you with technical knowledge, expertise and transferable skills in this exciting area. Our MRes will prepare you for an innovative research career at the interface between neuroscience and engineering, in academia, industry, or elsewhere. The programme comprises lectures, practical work and workshops in the first term, followed by full-time work on a research project<http://www.imperial.ac.uk/bioengineering/study/postgraduate-research/mres-n…>. In addition, you will attend regular seminars and a journal club throughout the year. Your research project will normally be supervised by a multidisciplinary team of at least two Imperial College London<https://www.imperial.ac.uk> supervisors who will bring technical and neuroscience expertise to the project. Careers The MRes Neurotechnology provides unique training at the interface between neuroscience and engineering, enhancing your skills in research, analysis and scientific presentation and developing your ability to work in a multidisciplinary team. Our programme provides a solid foundation in research for those continuing with a neurotechnology career, whether through a PhD or working in industry. How to apply Please visit our webpage<http://www.imperial.ac.uk/bioengineering/study/postgraduate-research/mres-n…> for full details of the course and how to apply, including entry requirements and projects available for 2020 entry<http://www.imperial.ac.uk/bioengineering/study/postgraduate-research/mres-n…>. The deadline for applications is 15 June, but applications are considered on a rolling basis, so we encourage you to apply now. ******************** Thank you. Best wishes, Andrei Kozlov (Director of the MRes in Neurotechnology)

May 21, 2020

DEPSCoR funding opportunity for tenured/tenure-track faculty in select US states/territories

by GREENWALD, HAL S DR-04 USAF AFMC AFOSR/RTA

The Defense Established Program to Stimulate Competitive Research (DEPSCoR) is a capacity building program that is designed to strengthen the research infrastructure at institutions of higher education in underutilized states/territories. Eligible applicants are full-time tenured or tenure-track faculty members at institutions of higher education in the following US states/territories: Alabama, Alaska, Arizona, Arkansas, Connecticut, Delaware, District of Columbia, Guam, Hawaii, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Mexico, North Dakota, Oklahoma, Oregon, Puerto Rico, Rhode Island, South Carolina, South Dakota, Tennessee, U.S. Virgin Islands, Vermont, West Virginia, Wisconsin, and Wyoming. Applicants must never have served as the PI on a prior DoD-funded award. Applicants must select a co-PI/collaborator who is a tenured or tenure-track faculty member at an institution of higher education in a DEPSCoR-eligible state/territory and has served as the PI on a DoD-funded research award active between 1 October 2013 and 30 September 2020. Awarded grants may be for up to $200,000 per year for three years. Topic areas: Air Force Office of Scientific Research: 1. Cognitive and Computational Neuroscience 2. Space Science 3. Agile Science of Test and Evaluation 4. Materials with Extreme Properties Army Research Office: 5. Propulsion and Energetics 6. Computational Architectures and Visualization 7. Optoelectronics 8. Probability and Statistics 9. Molecular Structure and Dynamics 10. Social and Behavioral Science 11. Biotronics Office of Naval Research: 12. Aerospace Structures and Materials 13. Ocean Acoustics 14. Machine Learning, Reasoning, and Intelligence 15. Power Electronics & Electromagnetism, Adaptive & Machinery Controls and Advanced Machinery Systems For complete details, please see the funding opportunity announcement at https://www.grants.gov/web/grants/view-opportunity.html?oppId=326765. White papers are due by 21 September 2020. Hal S. Greenwald, Ph.D. Program Officer, Cognitive & Computational Neuroscience Air Force Office of Scientific Research (AFOSR/RTA) 875 N. Randolph St. Arlington, VA 22203-1768 (703) 588-8441

May 20, 2020

PhD position Deep Learning for MRI-based addiction research

by Fabian Eitel

May 20, 2020

PostDoc in Reinforcement Learning for Intensive Care Treatment (including Covid-19) @ Imperial College London

by Faisal, Aldo A

Dear All, We are looking for a Post-Doctoral research fellow to join our machine learning effort to establish the computational foundations for an “AI clinician” (Komorowksi et Faisal, 2018, Nature Medicine; Li et Faisal, 2020, ICLR AI4Health). While a “fully autonomous doctor” is far more ambitious (and perhaps undesirable) than self-driving cars (Topol, 2019, Nature Medicine), our goal is to link our work in the established foundations of clinical decision recommendation systems and evaluate our developments in a meaningful clinical setting. This vision in turn requires the development of novel RL techniques, which are at the heart of this fellowship, such as causal inference in RL and explainable RL (XRL). We have previously shown that RL and Bayesian Optimization can be applied for learning optimal interventions in closed loop (Bohte et al, 2013, Lorenz et al, 2016). We work on methods allowing us to train RL agents interactively (off-policy policy estimation) on historical data of medical interventions (“actions”) and patient responses to them (“state”). We want to build on our groundwork drawing on causal inference, deep- and kernel-based machine learning (Liu et al, 2018, NeurIPS; Parbhoo et al, 2018, PLOS1; Peng et al, 2018, AMIA) and explainable RL (Shafti et al, IROS, 2019) for the emerging domain of RL for medical interventions. Crucially, we believe that Machine Learning for medical intervention may have a larger impact on health than diagnostics, as treatment is where medicine really starts helping people. Crucially, we are working on both the theory and application for RL in healthcare and have as a team already the necessary regulatory approvals for clinical evaluations in our university hospitals are in place and already recruited clinical staff and hospital IT teams. Moreover, as our domain application is the optimal treatment of patient intensive care units, the PostDoc will have the opportunity to join the fight against Covid-19 to save lives by better understanding. Our lab is leading the data science effort for the UK national service evaluation in critical care (https://www.imperial.ac.uk/artificial-intelligence/research/covid/covid-icu/) and is thus working on data from ICUs across an entire country to identify optimal treatment policies. Advert here: https://www.imperial.ac.uk/jobs/description/ENG01259/research-associate https://www.jobs.ac.uk/job/BZP190/research-associate Applications can be received after the advertised deadline (which will be also extended due to Covid-19). Please do reach out to me to find out more. kind regards Aldo -- Aldo Faisal Director, Centre in AI for Healthcare – https://ai4health.io Reader in Neurotechnology -- https://FaisalLab.org Data Science Institute, Dept. of Computing & Dept. of Bioengineering Imperial College London

May 20, 2020

PhD scholarship on spiking network computational models at Barcelona

by Xavier Otazu

The Neurocomputation and Biological Vision Team (NeuroBiT) (<http://www.cvc.uab.es/neurobit> ) offer a PhD scholarship to work in a highly multidisciplinary project which includes computational modelling of primary visual cortex and psychophysical experimentation of colour perception and its relationship to visual migraines. The Research will take place at the Computer Vision Centre <http://www.cvc.uab.es> (http://www.cvc.uab.es) of the Univ. Autònoma de Barcelona, which is consistently ranked among the top Spanish Universities <https://www.uab.cat/web/about-the-uab/the-uab/the-uab-in-the-rankings-13456…> (https://www.uab.cat/web/about-the-uab/the-uab/the-uab-in-the-rankings-13456…) The centre is located in a campus outside the vibrant city of Barcelona and has a strong tradition of multidisciplinary research in computational colour vision with their own psychophysical laboratory, living labs facilities and several computer clusters. The candidate will be part of the NeuroComputation and Biological Vision Team (NeuroBiT <http://www.cvc.uab.es/neurobit/> ), a recently-formed multidisciplinary research group which combines perceptual and computational approaches with visual neuroscience. We offer regular meetings with other PhD students, international contacts and the possibility of internship/cooperation with other experimental/theoretical labs. The successful candidate is likely to obtain several high-impact publications. The student research topic will be one of the following (to discuss with the candidate): 1) The development of recurrent multilayer spiking networks to reproduce the biological architecture of the primary visual cortex and several of its physiological properties, aiming at reproducing the results of psychophysical studies in colour perception and clinical studies on migraines. 2) Use of STDP (Spike Time Dependent Plasticity) for the definition of biologically plausible deep learning computational architectures (i.e. SNN –Spiking Neural Networks-). The duration of the position is 4 years (48 months). We expect the position to start on september/october 2020 (i.e. eventual visa issues should be solved beforehand!). The total annual stipend of the grant is around €15.000 gross, which include the cost of registration fees for the official doctorate program. Conditions: The candidate must * hold a European Higher Education Area (EHEA) qualification of at least 300 ECTS credits or a university-awarded Master degree or equivalent in the natural sciences/engineering at the time of signing the contract. * have experience in programming with Python and/or Matlab (C, C++, Unix environment and computer cluster experience are also valued) * have knowledge of / interest in the human visual system, visual perception and statistics * proficiency in English and Spanish * have excellent skills in analytical thinking, perceptiveness, commitment, self-organization, teamwork, and communication Any previous experience in the subject of computational modelling will also be a bonus. How to apply: Please send your CV and a short statement (500 words) connecting your previous work with the topics of this grant to xotazu(a)cvc.uab.es <mailto:xotazu@cvc.uab.es> and a copy of the official academic transcript (including GPA). We encourage candidates with strong skills in programming who are interested to work in a highly multidisciplinary project and environment (computer science, neuroscience, psychophysics), to apply. Candidates should have a degree in a related subject (Neuroscience, Computer Science, Mathematics, Physics, Biology, etc.).

May 18, 2020

Faculty position at CHAIN: Assistant Professor or Lecturer

by Hideaki Shimazaki

Dear colleagues, Our newly established Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN) at Hokkaido University in Japan invites applications for a faculty position at the Assistant Professor or Lecturer level. The full description and details are attached below. See also: https://jrecin.jst.go.jp/seek/SeekJorDetail?fn=3&ln=1&id=D120050453&ln_jor=1 https://www.chain.hokudai.ac.jp/?lang=en The deadline for applications is 8 June 2020 (JST). All the best, Hideaki --- Hideaki Shimazaki, Ph.D https://www.neuralengine.org Position Open: Assistant Professor or Specially Appointed Lecturer, Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN), Hokkaido University Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN), Hokkaido University, in Hokkaido, Japan invites applications for a 3.5 year research and teaching position with an anticipated start date of September 1st, 2020. The successful applicant will be appointed as a faculty member at the rank of Specially Appointed Assistant Professor or Lecturer in CHAIN. Women and members of other underrepresented groups are particularly encouraged to apply. CHAIN is a research and education center for interdisciplinary studies in the humanities, social sciences, neuroscience, and artificial intelligence. It aims to open up new directions of research into the nature of human existence by fostering interaction and collaboration between humanities and the social sciences, including philosophy, ethics, psychology (cognitive and social), law, and economics, and the natural sciences, such as neuroscience, AI, and cognitive science. In particular, it focuses on connecting philosophical ideas with methods and insights of mathematical and empirical sciences. A new interdisciplinary graduate program of CHAIN starts in July 2020. Qualifications The ideal applicant will have an independent research project that will strengthen and complement existing interdisciplinary research in CHAIN. They are expected to demonstrate the following qualities and characteristics: 1. A PhD by the time of the appointment in one (or more) of the following area(s): philosophy, ethics, psychology, cognitive science, neuroscience, AI, information science, or robotics. 1. Outstanding publication records and/or demonstrable potential to publish in highly esteemed publication outlets. 1. Strong motivation to fulfill research, teaching, and administrative duties as a faculty member in CHAIN. 1. Enthusiasm and competence for delivering postgraduate and undergraduate courses on topics pertinent to CHAIN’s research and education goals. 1. A demonstrated ability and strong interest to develop and engage in interdisciplinary research projects in collaboration with existing members of the institution. Application materials Submit the following materials, compiled in a single ZIP file, via email at jobs [at]chain.hokudai.ac.jp to complete your application: 1. Curriculum Vitae* 2. Summary of past research accomplishments (1-2 pages) 3. Three most important publications relevant to this position. 4. Brief statement of research and teaching interests (1-2 pages) 5. Two references (Names and contact details) Use common fonts such as Times New Roman in black and size 12 points. Submit each publication in a separate PDF file. Compile all the rest (1, 2, 4, and 5) in a single PDF file. This makes four PDF files in total, which must then be compiled in a single ZIP file. Submission is due Monday, 8 June, 2020 (JST). The subject line of the email must read “Application (Lecturer/Assistant Professor).” You will receive a confirmation email shortly after making a submission. Please contact us immediately if you did not receive one within 3 business days. Personal information obtained through these materials will only be used within this selection process. *Applicants who have been employed by Hokkaido University after April 1, 2014 (in any position, including Part-time Lecturer, Teaching Assistant, Teaching Fellow, Research Assistant and Short-term Support Assistant, etc.) should provide full details of their employment history in the CV. Appointment terms This is a full-time research and teaching position with an anticipated start date of September 1st, 2020. The salary will be paid under the annual-salary scheme and the discretionary labor system. The annual salary is determined in accordance with the internal regulations of Hokkaido University. Upon employment, one will be enrolled in the Ministry of Education, Culture, Sports, Science and Technology Mutual Aid Association, Employees Pension, Workers’ Accident Compensation Insurance and Employment Insurance. A one month probationary period applies. Questions about the position should be addressed to the chair of the search committee, Shigeru Taguchi (inquiry[at]chain.hokudai.ac.jp). Further information Website: www.chain.hokudai.ac.jp/?lang=en Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN) Hokkaido University Kita 12 Nishi 7, Kita-ku, Sapporo Hokkaido 060-0812 Japan Application submission: jobs [at] chain.hokudai.ac.jp Inquiries: : inquiry [at] chain.hokudai.ac.jp

May 15, 2020

PhD position in computational neuroscience and robotics

by Xavier Hinaut

A PhD position is available at the Inria Bordeaux Sud-Ouest center and the Institute of Neurodegenerative Disease in Bordeaux, France. What: PhD position in computational neuroscience and robotics Where: Inria, Bordeaux, France When: October 2020 (3 years duration) Who: Xavier Hinaut & Frédéric Alexandre Application deadline: May 22th (22/05/2020) How to apply: https://jobs.inria.fr/public/classic/en/offres/2020-02637 Title of the PhD topic ================= NewSpeak: Neuro-computational models of language comprehension and production grounded in robots Keywords ================= Recurrent Neural Network (RNN), Reservoir Computing, Developmental Language Learning, Neuro-Robotics, Multimodal Language Grounding, Computational Neuroscience, Reinforcement Learning Candidate profile ================= - Good background in maths and computer science; - A strong interest for neuroscience and the physiological processes underlying learning; - Python programming with experience in scientific libraries Numpy/Scipy (or similar coding language: matlab, etc.); - Experience in machine learning or data mining is a preferred; - Independence and ability to manage a project; - Good English reading/speaking skills. Proposed research ================= We target to embody models into robots that will developmentally ground language. The grounding of semantics should come from the robot experiencing the world through its interactions with humans and the physical world. The goals are (1) to test hypotheses with biologically plausible language learning models with the Nao robot, (2) to extend the current model with unsupervised training and by reinforcement learning, and (3) to propose a new kind of Generative Adversarial Networks (GANs) for developmental language learning conditioned by grounded modalities such as vision. In order to model how a sentence can be processed, word by word (Hinaut & Dominey 2013) or even phoneme by phoneme (Hinaut 2018), the use of recurrent (artificial) neural networks, such as Reservoir Computing, offers interesting advantages. In particular the possibility to compare the dynamics of the model with data from neuroscience experiments (EEG, fMRI, ...). This paradigm allows to learn with few learning examples, and offers negligible runtime for human-robot interactions. The use of linguistic models with robots is not only useful to validate the models in real conditions, it also allows to test other hypotheses, notably on the anchoring of the language or the emergence of symbols. This involves finding out how a learning agent can link and categorise physical stimuli (vision, hearing, proprioception, etc.) to make the correspondence with symbols (Harnard 1990), or even to make these symbols emerge from stimuli coming from sensors (Taniguchi et al. 2016). We aim that a robot could process language from morphemes to sentences, similarly as a child, in order to better model how children acquire language. One aim is to obtain symbolic representations that are a composition of multimodal grounded representations. We will experiment how the newly developed language model will be able to learn to understand utterances by exploring which meanings the morphemes, words, ... can have based on other modalities of the robot (e.g. vision, proprioception). Starting from preliminary results (Juven & Hinaut 2020), we will first consider merging the representations from vision with a pre-trained CNN (Convolutional Neural Network). Then, reinforcement learning experiments will explore how the robot can learn the meaning of sentences: first by doing random actions for any user utterance, and then bootstrap from the user’s feedback. We will use a concrete corpus of sentences based on actions a robot can do (Hinaut & Twiefel 2019). We will implement several variants of language models: (1) extension of the reservoir computing model linked with grounded CNN, (2) adapt such model to the GAN paradigm in order to couple language comprehension and production in a self-learning generative mechanism (thus creating more biologically plausible GANs), (3) explore unsupervised (cross-situational learning) and reinforcement learning with these models. In parallel, we will adapt models features and behaviours to the ones observed in language acquisition experiments in psychology, and neural evidences in neuro-linguistic studies. In particular, we will explore how the models could shed light on language developmental impairments. We will run models in simulated humanoid robots and in a Nao robot. More information ============ More information is available on the application web page: https://jobs.inria.fr/public/classic/en/offres/2020-02637 Questions can be asked by email to Xavier Hinaut (xavier.hinaut(a)inria.fr) Xavier Hinaut Inria Researcher (CR) Mnemosyne team, Inria LaBRI, Université de Bordeaux Institut des Maladies Neurodégénératives +33 5 33 51 48 01 www.xavierhinaut.com

May 15, 2020

Postdoc position in the Mainen lab at Champalimaud

by Luca Mazzucato

Systems Neuroscience Postdoctoral Fellow The Champalimaud Foundation, a private, non-profit research institution, is opening a call for a post-doctoral researcher, within the scope of the research project entitled "Neural mechanism of value based decision making of staying or leaving - Deciding when to initiate locomotion to move to the next reward location." This position involves data analysis/modeling of foraging behavior and self-initiated movements in rodents, related to a Systems Neuroscience experiment addressing the following question. When interacting with a complex environment, animals generate naturalistic behavior in the form of action sequences. To analyze and classify such behavior from video recordings is a computationally demanding task, requiring development of specific software pipelines adapted for big data structures using deep learning methods and state space models. This project aims at creating such a pipeline for analyzing videos of mouse behavior previously collected in the Mainen Lab at the Champalimaud Center for the Unknown, Portugal. In the experiment, animals performed certain action sequences, with variable onsets timing, leading to a water reward. Optogenetics photostimulation of inhibitory neurons in secondary motor regions was also performed during selected action sequences. Behavior during this task was recorded with two high speed, high resolution cameras pointing at the animal's face and front limbs. The large size of the datasets generated in this experiment (~1 Tb per animal, for 10 animals) requires an extensive effort to classify behavioral motifs. In the second part of the project, behavioral motifs will be related to large scale recordings of neural activity from Neuropixel probes. The fellow will investigate the relationship between neural activity and behavior using state space models and mechanistic models based on recurrent neural networks. The fellow will integrate a dynamic team of researchers as part of an international collaboration between the Mainen Lab <https://mainenlab.org/> at the Champalimaud Centre for the Unknown and the Mazzucato Lab <https://www.mazzulab.com/> at University of Oregon. National, foreign and stateless candidates can develop the proposed work remotely where team interaction is supported by online platforms (e.g. slack, zoom, etc). *References:* Recanatesi, S. et al., biorxiv (2020). Vertechi, P. et al., Neuron (2020). Murakami, M. et al., Neuron (2017). Murakami, M. et al., Nat. Neuro (2014). Essential qualifications: PhD in Neuroscience, Cognitive Science, Biology, Experimental Psychology, Engineering, Physics, Mathematics, or other areas relevant to neurophysiology and animal behavior; Proficiency in Python and Matlab programming language and familiarity with object oriented programming; Familiarity with Deep Learning software (TensorFlow); Familiarity with data analysis of biological experiments; Ability to work independently and troubleshoot technical issues; Good capacity and value for teamwork and communication skills; Fluency in English. REMUNERATION The monthly remuneration to be attributed is the 33rd level of the single remuneration table (TRU), approved by Portaria nº 1553-C/2008, of December 31st, starting at a base gross salary of 2,128.34 Euros. SELECTION PROCESS Applications will be accepted until June 15th, 2020 or until a qualified candidate is hired. Candidates must submit a single document (maximum 4 pages; paper or PDF file) that contains a motivation letter and the Curriculum Vitae, both written in English. Email applications must be addressed to careers(a)research.fchampalimaud.org and include “CPD2020-LOCODECISION” in the subject line. The selected candidate must submit proof of her/his PhD or Doctoral Degree within 10 days following notification of the preliminary results. More information about Diplomas recognition may be found in the Euraxess portal <http://www.euraxess.pt/portugal/information-assistance/recognition-diplomas> . All candidates who formalize their application incorrectly or who fail to provide the requirements imposed by this tender are excluded from admission. In case of doubt, the panel is entitled to request further documentation to support candidate statements. Notification of Results: The highest scoring candidate will be notified by email or telephone. All other candidates will be notified solely by email. Non-discrimination and equal access policy: The Champalimaud Foundation actively promotes a policy of non-discrimination and equal access, so that no candidate can be privileged, benefited, harmed or deprived of any right, on basis of age, sex, sexual orientation, marital status, family status, economic situation, education, social origin or condition, genetic heritage, reduced working capacity, disability, chronic illness, nationality, race, territory of origin, language, religion, political or ideological convictions, and trade union membership.

May 14, 2020

Call for 22 PhD positions in BioRobotics at the BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy

by Calogero Maria Oddo

************************************* 22 PhD positions in BIOROBOTICS open! https://www.santannapisa.it/sites/default/files/flyer_phd_biorobotica_2020_…. ************************************* The PhD Program in BioRobotics is a three-year course managed by the BioRobotics Institute (http://sssa.bioroboticsinstitute.it) in the Department of Excellence in Robotics & AI, at Sant’Anna School of Advanced Studies, in Pisa (Italy). The PhD in BioRobotics is one of the largest doctoral schools worldwide in biomedical engineering and robotics, with about 100 PhD students enrolled. All positions are fully funded by Sant'Anna and the Italian Institute of Technology.The number of positions awarded could be expanded with additional fellowships that may be available before the start of the PhD course in October 2020. The students are educated in a stimulating and multidisciplinary environment, both through high-level courses and through demanding, creative and original research work. PhD projects are carried out in very well equipped, state-of-the-art laboratories (in such fields as micro-engineering, biomedical engineering, biomimetic and soft robotics, rehabilitation technologies, surgical robotics and neural engineering, robot companions) and through individual and team work performed under the supervision of a full-time faculty. ADMISSION: Students are admitted to the PhD Program following a successful entrance examination. Eligible applicants must hold a Master of Science (M.Sc.) degree or equivalent. Undergraduate students may also apply if they graduate within Oct. 31, 2020. START: Oct. 1, 2020 CALL details: https://www.santannapisa.it/en/admissions/call-admission-phd-biorobotics-3 APPLY at: www.santannapisa.it/en/education/phd-biorobotics DEADLINE: June 3, 2020 CONTACT: PhDBiorobotics(a)santannapisa.it Best regards, Calogero Oddo, on behalf of the PhD Board -- Calogero M. Oddo PhD BioRobotics, MSc and BSc Electronic Engineering Associate Professor of Bioengineering https://www.santannapisa.it/en/calogero-maria-oddo Vice-Coordinator of the PhD programme in BioRobotics Sant'Anna School of Advanced Studies, Pisa, Italy https://www.santannapisa.it/en/education/phd-biorobotics Head of the Neuro-Robotic Touch Laboratory, Neuro-robotics Area, The BioRobotics Institute Viale Rinaldo Piaggio 34, 56025, Pontedera (PI), Italy Sant'Anna School of Advanced Studies, Pisa, Italy http://www.santannapisa.it/en/neuro-robotic-touch-laboratory Department of Excellence in Robotics & AI Sant'Anna School of Advanced Studies, Pisa, Italy Piazza Martiri della Libertà, 33 - 56127 Pisa, Italy https://www.santannapisa.it/en/robotics-ai IEEE Senior Member, Founding Vice-Chair of the Italian Chapter of the IEEE Sensors Council (2018-20) http://sites.ieee.org/italy-sensors/about-ieee Office: +39050883067; Mobile: +393316992273; email:calogero.oddo@santannapisa.it -- Questa e-mail è stata controllata per individuare virus con Avast antivirus. https://www.avast.com/antivirus

May 13, 2020

Visiting Assistant Professor Position in Applied Mathematics at Northwestern University

by William L. Kath

Visiting Assistant Professorship in Applied Mathematics The Department of Engineering Sciences and Applied Mathematics at Northwestern University invites applications for the position of Visiting Assistant Professor in Applied Mathematics. This is a one-year, non-tenure-track position with the possibility of renewal for a second year. Duties involve teaching and research in applied mathematics with a focus on applications in engineering and/or the sciences. More information about this position can be found at: https://www.mccormick.northwestern.edu/applied-math/open-positions.html The Department seeks outstanding candidates who have received a Ph.D. degree in applied mathematics, engineering, physics or another applied math-related discipline, or who expect to do so by July 2020, and who aspire to engage in independent and interdisciplinary research and teaching. The starting date is September 1, 2020. The application package should include a cover letter, curriculum vita, statement of research accomplishments and interests, statement of teaching experience and philosophy, and if available a representative manuscript (published, submitted or in preparation). The application should be submitted online at: https://facultysearch.mccormick.northwestern.edu/apply/index/MTAz In addition, the applicant should arrange for at least two, but no more than three letters of recommendation addressing both research and teaching qualifications. Recommendation letters will be automatically solicited from the letter writers by email after the names are entered in the online application system. Questions may be directed to Meelee Ahn Park at meelee.park(a)northwestern.edu <mailto:meelee.park@northwestern.edu> (Subject line: Visiting Assistant Professor Search). To ensure full consideration, applications should be received by May 15th, 2020, but applications will be accepted until the position is filled. Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States. Engineering Sciences and Applied Mathematics Northwestern University 2145 Sheridan Road, Room M426 Evanston, IL 60208-3125, USA esam(a)northwestern.edu <mailto:esam@northwestern.edu> Phone: (847) 491-3345 -- William L. Kath Co-Director, NSF-Simons Center for Quantitative Biology Professor, Engineering Sciences and Applied Mathematics McCormick School of Engineering, Northwestern University 2145 Sheridan Road, Evanston, IL 60208-3125 Phone: 847-491-8784 Fax: 847-491-2178

May 13, 2020

International Symposium on Artificial Intelligence and Brain Science 2020 in Tokyo

by Kenji Doya

We are pleased to announce a symposium that brings together researchers in the forefront of AI and neuroscience. Application for poster presentation is open till June 1st and general registration will start from July 1st, 2020. ******** International Symposium on Artificial Intelligence and Brain Science Date: October 10-12 (Sat-Mon), 2020 Venue: Ito Hall, The University of Tokyo, Japan Web site: http://www.brain-ai.jp/symposium2020/ Program (it may be held online depending on the COVID-19 situation) • Saturday, October 10th (from 1pm) Keynote: Josh Tenenbaum (MIT) Session 1: Deep Learning and Reinforcement Learning Yann LeCun (NYU, Facebook), Yutaka Matsuo (U Tokyo), Doina Precup (McGill U) David Silver (DeepMind), Masashi Sugiyama (RIKEN AIP/U Tokyo IRCN) • Sunday, October 11th Session 2: World Model Learning and Inference Ila Fiete (MIT), Karl Friston (UCL), Yukie Nagai (U Tokyo IRCN) Maneesh Sahani (Gatsby Unit), Tadahiro Taniguchi (Ritsumeikan U) Poster Session Session 3: Metacognition and Metalearning Matthew Botvinick (DeepMind), Ryota Kanai (ARAYA), Angela Langdon (Princeton U) Hiroyuki Nakahara (RIKEN CBS), Xiao-Jing Wang (NYU) • Monday, October 12th Session 4: AI for Neuroscience and Neuromorphic Technologies Jim DiCarlo (MIT), Yukiyaku Kamitani (Kyoto U), Rosalyn Moran (King’s College London) Terry Sejnowski (Salk Institute), Hidehiko Takahashi (Tokyo MDU) Session 5: Social Impact and Neuro-AI Ethics Anne Churchland (CSHL), Kenji Doya (OIST), Arisa Ema (U Tokyo IFI) Hiroaki Kitano (SONY CSL), Stuart Russell (UC Berkeley) Poster Registration: May 11th - June 1st (review result notified by June 20) General Registration: July 1st - 31st (or when the capacity is reached) Please check the web site: http://www.brain-ai.jp/symposium2020/ Sponsor: KAKENHI Project on Artificial Intelligence and Brain Science (http://www.brain-ai.jp) Co-sponsors: RIKEN AIP (https://aip.riken.jp/?lang=en) U Tokyo IFI (https://ifi.u-tokyo.ac.jp/en/) U Tokyo IRCN (https://ircn.jp/en/) Contact: ncus(a)oist.jp ---- Kenji Doya <doya(a)oist.jp> Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University 1919-1 Tancha, Onna, Okinawa 904-0495, Japan Phone: +81-98-966-8594; Fax: +81-98-966-2891 https://groups.oist.jp/ncu

May 13, 2020

Dual-award PhD in Neuromorphic Olfaction (UH/WSU)

by Michael Schmuker

We’re looking for an outstanding candidate to enter a Dual-PhD programme on Neuromorphic Olfaction. The successful candidate will pursue a PhD in the BioMachineLearning lab at the University of Hertfordshire (UK), and the International Centre for Neuromorphic Systems (ICSC), at Western Sydney University, Australia. The successful candidate will develop event-based algorithms for Neuromorphic olfaction, in close collaboration with Neuromorphic hardware developers and computational neuroscientists. In this unique opportunity, the candidate is eligible to obtain a PhD award from both universities, UH and WSU. It’s a fully funded programme that covers also travel expenses between UH and WSU. Interested? Get in touch! More info: https://biomachinelearning.net/positions <https://biomachinelearning.net/positions> — Dr Michael Schmuker AFHEA Reader in Data Science Biocomputation Group University of Hertfordshire https://biomachinelearning.net <https://biomachinelearning.net/>

May 12, 2020

[jobs] Postdoctoral position in: Cognition for safety and ergonomics for human-robot interaction in manufacturing workspaces - [ Postdoc ]

by Francesco Rea

The COgNiTive Architecture for Collaborative Technologies Research Line at Istituto Italiano di Tecnologia in Genoa - Center for Human Technologies, is opening one postdoctoral position focusing on the assessment of engagement with safety and ergonomic work, design of proactive measures and counter measures for safety preservation, optimization of ergonomics, design of software infrastructure for social interaction and safety-ergonomic preservation. The research activities will be carried out under the supervision of Dr. Alessandra Sciutti and Dr. Francesco Rea (Participant Manager within the Steering Board -SB). The selected candidate will work with a multidisciplinary consortium of participant to the awarded project APRIL (H2020, n. G.A. 870142). APRIL project aims at implementing and deploying market oriented, low cost and multipurpose robots that supports semiautomatic tasks in manufacturing production lines and handle flexible or deformable materials in industries of any size or domain. The candidate will work with different robotic platforms for human-robot interaction in manufacturing context selected together with the consortium and with different sensorial setups specifically designed to assess the gaze pattern, reaction time, working movements, fatigue level in workers. https://www.iit.it/careers/openings/opening/1198-postdoctoral-position-in-c… The activity will be carried out within the implementation of the APRIL project in a fully equipped laboratory, including motion capture and eye-tracking devices, and in a team with a variety of competences ranging from robotics to designing of experimental studies on humans. The research for this Postdoctoral position will involve: * Sensing of human working conditions for social, safe and ergonomic based activities on human-robot collaboration * Design of control systems for Safety in human-robot collaboration * Development of a system improving human-robot social collaboration in manufacturing context * Development of a system improving ergonomics and mitigating health and safety risks The first goal of the research is redesigning cognition for safety and ergonomics for human-robot collaboration in manufacturing workspaces. The second goal of technological implications is to support the design of new multipurpose robotics for manipulation of deformable materials in manufacturing processes. The successful candidate will be offered a salary commensurate to experience and skills. Interested applicants should submit CV, list of publications, name and contacts of 2 referees and a statement of research interest to jobpost.78417(a)iit.it<mailto:jobpost.78417@iit.it> by May 20, 2020 quoting Postdoctoral position in "Cognition for safety and ergonomics for human-robot interaction in manufacturing workspaces - CB 78417" in the subject line.

May 10, 2020

Research Assistant (Research Associate)

by Artur Luczak

Research Assistant (Research Associate) at the University of Lethbridge. Our lab seeks a highly motivated individual with a strong computational background to work at the interface of neuroscience and machine learning. We are especially interested in the application of deep neural networks to improve our understanding of neuronal data, and the application of recent neuroscience findings to improve the performance of deep neural networks. In our lab we also record the activity of hundreds of neurons in normal and epileptic animals, and the successful candidate is welcome to participate in those projects. Preferred candidate should have strong background in modeling neurons and networks, and should be very familiar with models of synaptic plasticity (e.g. BCM). Our lab at the Canadian Centre for Behavioural Neuroscience in the University of Lethbridge is located in the sunniest area of Canada and next to scenic Rocky Mountains. All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority. For more information please visit our website at: http://lethbridgebraindynamics.com/artur_luczak. Duties and responsibilities: - Conduct research and literature reviews, in related topics for use in scholarly publications. - Compile research results and assist professors in the analysis of results and the preparation of journal articles or papers. - Analyze data using statistics, programming techniques and artificial neural networks. - Develop analytical methods in biologically plausible artificial neural networks. - Participate in scientific discussion groups and seminars. All duties and responsibilities shall be carried out under the supervision of Prof. Artur Luczak. Skills & Qualifications: - Master degree’s in neuroscience, physics, computer science or related topics. - 3 years of related research work experience. - Having strong background in modeling neurons and networks, and should be very familiar with models of synaptic plasticity. - Familiarity with epilepsy is an asset - Highly experienced in programming with Python and Matlab. - Ability to work with data, applying machine learning methods and deep learning. - Working with computer clusters and cloud computing. - Excellent communication and team work skills. Working Conditions: Work in an office with a computer provided. Hours of Work: Full-time, 30-32 hours per week. Salary: $21.63 /hour Duration: one year with the opportunity for extension Language requirements: English Benefits: Standard benefits including Extended Health, Dental, EFAP, Life Insurance and Long Term Disability. Interested applicants are encouraged to contact Professor Artur Luczak (Luczak(a)uleth.ca) with a copy of their CV and a cover letter. Address: University of Lethbridge. 4401 University Drive West, Lethbridge, Alberta T1M 1R6, Canada

May 10, 2020

Call for papers MLCN at MICCAI 2020

by MLCN Workshop

*Please find below the call for papers for the International Workshop of Machine Learning in Clinical Neuroimaging (MLCN) on 4 October 2020 at MICCAI 2020 in Lima, Peru. We welcome contributions on novel machine learning methods and their applications to clinical neuroimaging data.* The submission deadline is *30 June 2020*, and all MLCN accepted papers will be eligible for the best paper award of 500 USD. For more information, please visit https://mlcnws.com/. Best wishes, The MLCN 2020 committee Christos Davatzikos Andre Marquand Jonas Richiardi Emma Robinson Ahmed Abdulkadir Cher Bass Mohamad Habes Seyed Mostafa Kia Jane Maryam Rondina Chantal Tax Hongzhi Wang Thomas Wolfers International Workshop on Machine Learning in Clinical Neuroimaging 4 October 2020 in Lima, Peru The International Workshop of Machine Learning in Clinical Neuroimaging ( https://mlcnws.com/) a satellite event of MICCAI (https://miccai2020.org) calls for original papers in the field of clinical neuroimaging data analysis with machine learning. The two tracks of the workshop include methodological innovations as well as clinical applications. This highly interdisciplinary topic provides an excellent platform to connect researchers of varying disciplines and to collectively advance the field in multiple directions. For the machine learning track, we seek contributions with substantial methodological novelty in analyzing high-dimensional, longitudinal, and heterogeneous neuroimaging data using stable, scalable, and interpretable machine learning models. Topics of interest include but are not limited to: - Spatio-temporal brain data analysis - Structural data analysis - Graph theory and complex network analysis - Longitudinal data analysis - Model stability and interpretability - Model scalability in large neuroimaging datasets - Multi-source data integration and multi-view learning - Multi-site data analysis, from preprocessing to modeling - Domain adaptation, data harmonization, and transfer learning in neuroimaging - Unsupervised methods for stratifying brain disorders - Deep learning in clinical neuroimaging - Model uncertainty in clinical predictions - ... In the clinical neuroimaging track, we seek contributions that explore how the application of advanced machine learning methods help us to move towards precision medicine for complex brain disorders. Topics of interest include but are not limited to: - Biomarker discovery - Refinement of nosology and diagnostics - Biological validation of clinical syndromes - Treatment outcome prediction - Course prediction - Analysis of wearable sensors - Neurogenetics and brain imaging genetics - Mechanistic modeling - Brain aging - ... Submission Process: The workshop seeks high quality, original, and unpublished work that addresses one or more challenges described above. Papers should be submitted electronically in Springer Lecture Notes in Computer Science (LCNS) style (see https://www.miccai2020.org/en/PAPER-SUBMISSION-GUIDELINE.html#manuscript-fo… for detailed author guidelines) using the CMT system at https://cmt3.research.microsoft.com/MLCN2020. The page limit is 8-pages (text, figures, and tables) plus up to 2-pages of references. We review the submissions in a double-blind process. Please make sure that your submission is anonymous. Accepted papers will be published in a joint proceeding with the MICCAI 2020 conference. Best Paper Award: This year, all MLCN accepted papers will be eligible for the best paper award. The recipient of the award will be chosen by the MLCN scientific committee based on the scientific quality and novelty of contributions. The winner will be announced at the end of the workshop and will receive 500 USD honorarium. Important Dates: - Paper submission deadline: June 30th, 2020 - Notification of Acceptance: July 24th, 2020 - Camera-ready Submission: July 31st, 2020 - Workshop Date: 4 October 2020

May 8, 2020

PhD position at EPFL (Lausanne, Switzerland)

by Milekovic Tomislav

PhD position in the lab of Prof. Gregoire Courtine at EPFL (Lausanne, Switzerland) A computational approach to personalize and optimize clinical treatments for restoring locomotion to people paralyzed by spinal cord injury 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. In addition, PhD salaries at EPFL rank the highest in the world. 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 could 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 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 individual persons' spinal columns from MRI scans 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 Finite Element Models, compartmental cable models, neurobiomechanical models and Machine Learning Contact: Applications including a CV and a cover letter should be sent to andreas.rowald(a)epfl.ch

May 8, 2020

Fully-funded PhD Positions in Biomedical Imaging Computing, Lehigh University, USA

by Yu Zhang

*Fully-funded PhD Positions in Biomedical Imaging Computing, Lehigh University, USA* The Biomedical Imaging and Computation Laboratory (BIC Lab) at Lehigh University (Bethlehem, USA) is currently accepting applications for PhD positions in biomedical imaging computing. *Position description: *The research project will focus on developing and applying a variety of machine learning/deep learning methods for biomedical imaging analysis and prediction. The successful applicants will contribute to research and development in artificial intelligence (AI)-driven neural biomarker discovery using advanced neuroimaging techniques (e.g., MRI and EEG) for precision medicine of brain diseases. *Qualifications: *Successful applicants will have a Bachelor’s or Master’s degree in Electrical Engineering, Biomedical Engineering, Computer Science, or other related fields, and strong motivation to do high-quality research in novel biomedical imaging computing with machine learning. Additionally, strong quantitative skills and a programming background (Matlab and/or Python) are important. Previous research experiences in related fields and scientific publications in journals/conferences are preferred. *Lehigh University: *Lehigh University is a premier research university in the United States, consistently ranked in the top tier of national research universities each year. It is a coeducational, nondenominational, private university that offers a distinctive academic environment for undergraduate and graduate students from across the globe. Located in Pennsylvania’s scenic Lehigh Valley, the campus is situated on 1,600 acres in close proximity to both New York City and Philadelphia. The application materials will be reviewed immediately once received. The expected starting time is Fall 2020 or Spring 2021. Interested candidates should send a cover letter describing your research interests, CV (including undergraduate GPA and ranking, transcripts if applicable), and contact information of three references to Dr. Yu Zhang at yzhangsu(a)stanford.edu and zhangyubrain(a)gmail.com. Check here for detailed admission requirements (e.g., GRE and TOEFL scores) https://engineering.lehigh.edu/bioe/graduate/bioengineering-admissions-guid… -- Yu Zhang, PhD Assistant Professor Department of Bioengineering, Lehigh University Research Fellow Wu Tsai Neurosciences Institute, Stanford University Webpage: http://yuzhangresearch.weebly.com/ Email: yzhangsu(a)stanford.edu

May 7, 2020

Neuromatch 2.0 – an online unconference in neuroscience, May 25-27, 2020

by Grace Lindsay

Announcing Neuromatch 2.0 – an online unconference in neuroscience, May 25-27, 2020. After a successful two-day conference in March, Neuromatch is back for three days this May! This fully online computational neuroscience conference will include invited and submitted talks, a virtual poster session, panels, debates, group discussion, and “mind-matching” events. In partnership with the IEEE Brain Initiative, one day of the conference will focus on neural data analysis. In partnership with eLife, Neuromatch will also feature talks and discussion with early career researchers. Registration and talk/poster submissions are due May 20th. For instructions on how to submit, please see: https://neuromatch.io/instructions/ For more information and to register for the conference, visit our site: https://neuromatch.io/ If you want to participate in the “mind-matching” or group discussion events (where you’ll be algorithmically paired with other scientists based on mutual research interests), don’t forget to include example abstracts so we know your interests! Confirmed Speakers: - Eve Marder (Brandeis University) - Jenny Bizley (UCL) - Richard Naud (U of Ottawa) - Yael Niv (Princeton) - Jakob Macke (TU of Munich) - Asya Rolls (Technion) - Joseph Raimondo (U of Cape Town) - Dan Yamins (Stanford) - Demba Ba (Harvard) - Ilana Witten (Princeton) - Eugenia Chiappe (Champalimaud) - Byron Yu (CMU) - Adrienne Fairhall (U of Washington) - Polina Anikeeva (MIT) Sincerely, Neuromatch 2.0 organizers Dan Goodman (Imperial) Konrad Kording (UPenn) Brad Wyble (Penn State) Titipat Achakulvisut (UPenn) Tim Vogels (Oxford) Chris Rozell (Georgia Tech) Yiota Poirazi (IMBB/FORTH) Grace Lindsay (UCL)

May 7, 2020

Two Post-doc opportunities in machine learning for neurological conditions

by Andre Altmann

Dear Comp-Neuro Community, If you like the challenge of developing novel computational and mathematical solutions to real-world medical challenges, then you will love working with us in the UCL Centre for Medical Image Computing (CMIC) [1] in London, UK. We are looking for two excellent postdoctoral researchers to join the UCL POND[2] team's well-established, supportive, expanding team of computational scientists in developing state-of-the-art data-driven solutions for neurological conditions like Alzheimer’s disease. In this field we lead international initiatives such as EuroPOND[3], TADPOLE Challenge[4], and the new E-DADS consortium[5]. Importantly, we ensure impact by collaborating closely with clinical scientists on our doorstep in London and our network of collaborators across the globe. *Deadline for applications is 25th May*. For details on the roles and to apply: http://pond.cs.ucl.ac.uk/vacancies Best wishes, Andre Altmann Links: [1] https://www.ucl.ac.uk/medical-image-computing/ [2] http://pond.cs.ucl.ac.uk/ [3] http://europond.eu/ [4] https://tadpole.grand-challenge.org/ [5] https://e-dads.github.io/

May 7, 2020

Postdoctoral Associate in Computational Neuroscience of Learning and Memory

by Yuri Dabaghian

*Postdoctoral Associate in Computational Neuroscience of Learning and Memory* A NSF-funded postdoctoral position is immediately available in the group of Dr. Yuri Dabaghian at the University of Texas in Houston. The goal of the projects is to understand the hippocampal mechanisms of learning and memory using computational topological and geometric approaches, neuronal network theory. The projects involve both computational modeling and analyses of in-vivo electrophysiological data provided by experimental collaborators. The ideal candidate should have a strong in background Computational Neuroscience, Applied Mathematics, Theoretical Physics or similar. To apply, please send a CV, letter of motivation and the names of two-three references to Yuri Dabaghian (Yuri.A.Dabaghian(a)uth.tmc.edu) Applications will be accepted until the position is filled.

May 4, 2020

Fully funded 4-year PhD Position at IIT - Computational approaches to study the neural code

by Stefano Panzeri

Fully funded 4-year PhD Position at IIT - Computational approaches to study the neural code We are seeking candidates for a fully funded 4-year PhD position at the Italian Institute of Technology’s in the lab directed by Stefano Panzeri ( https://www.iit.it/people/stefano-panzeri) We are particularly interested in candidates that wish to work in a project in collaboration with the experimental neurophysiology laboratory of Giuliano Iurilli (https://www.iit.it/people/giuliano-iurilli) We are interested in using mathematical models of neural networks and information theoretic and machine learning analytical tools to understand the principles of neural coding by using as a model the olfactory system. For recent representative publications of Panzeri and Iurilli on relevant topics please see: Chong et al, in press, preprint available at https://www.biorxiv.org/content/10.1101/841916v1 van Vugt B, et al, (2018) Science: DOI: 10.1126/science.aar7186 Runyan C. A., et al (2017) Nature: 548: 92-96 Panzeri, S, et al (2017) Neuron 93: 491-507 Iurilli, G. and Datta, R.S. (2017) Neuron 93 , 1180-1197 Safaai, H. et al (2015) Proc. Natl. Acad. Sci. USA 112(41): 12834–12839 The ideal candidate should have a strong background in numerate sciences, and have a strong propensity for interdisciplinary research. No extensive previous experience in neuroscience is needed. However, a keen interest in understanding the brain is essential. The deadline for the formal application is set to May 27th 2019, but interested candidates are invited me to contact us informally by email ( stefano.panzeri(a)iit.it and Giuliano.urilli(a)iit.it ) as soon as possible, and *no later than May 11th 2020,* by attaching their CV and briefly explaining their interest in this position, to initiate discussion about potential PhD projects of interest. Yours truly, Stefano Panzeri

May 4, 2020