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Open position: MIT, Co-instructor and education support coordinator in computational neuroscience
by Ila Fiete Nov. 5, 2019

Nov. 5, 2019

Dear Colleagues, I would appreciate if you would pass along to appropriate candidates the following advertisement for an open position for a Co-instructor and education support coordinator in computational neuroscience at MIT. Apologies if you receive multiple postings. Best wishes, Ila Fiete ------------------------------------------------ COMPUTATION COURSE CO-INSTRUCTOR AND EDUCATION SUPPORT COORDINATOR, MIT Brain and Cognitive Sciences, to support the development and instruction of computational courses (85%) and provide assistance to the department as a whole on enhancing and evaluating the quality of its undergraduate course offerings (15%). The goal will be to integrate computational thinking skills across the Course 9 curriculum and in the new Computation and Cognition (Course 6-9) curriculum, and provide innovative training in the areas of computational neuroscience, neuroengineering, and human and machine intelligence. The main responsibility will be to develop learning content for MIT students in these areas, including instructional videos, tutorials, problem sets, demonstrations of basic neuroscience and data analysis methods. Will hold office hours and give in-class lectures as appropriate and provide feedback and guidance before and after a course launches to ensure a high-quality learning experience. Will also provide support to the department in enhancing and evaluating the undergraduate program broadly, including assisting with website content (e.g., videotapes of classroom instruction, faculty/student interactions, etc.) and coordinating with the Teaching and Learning Laboratory to evaluate the efficacy of the department’s approaches to improving undergraduate education; and perform other duties as requested. Job Requirements REQUIRED: Ph.D. in neuroscience, bioengineering, computational cognitive science or related/equivalent area; at least one year of teaching experience; proficiency with MATLAB and Python; excellent communication skills; and a demonstrated commitment to undergraduate education. Web publishing experience a plus; as is knowledge of Dreamweaver, Photoshop, InDesign, Fetch, and HTML coding. Job #17993. Link: https://careers.peopleclick.com/careerscp/client_mit/external/jobDetails/jo…

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Data Scientist Position at Boston University
by Chen, Jerry Nov. 5, 2019

Nov. 5, 2019

The Lab of Jerry Chen at Boston University is hiring a Data Scientist to be involved in several multi-year BRAIN Initiative related NIH and NSF funded projects. These projects focus on understanding cortical computation during behavior by combining large-scale population recordings, anatomical reconstructions, and transcriptional profiling as well as developing tools for large-scale and high-speed imaging of neuronal populations. This person will be involved in help to analyze experimental data, developing software tools to aid in the data analysis, and helping with data infrastructure and management. Specific Projects include: 1. Analysis of dense electron microscope reconstructions of neuronal connectivity (ie. Connectomics) 2. Establishing pipeline for image analysis for in situ sequencing of gene expression 3. Establishing pipeline for automated behavioral training and analysis. 4. Visualization and analysis of population imaging data across multiple brain areas during behavior. This person will be jointly involved and mentored by personnel from the Hariri Institute's Software & Application Innovation Lab (SAIL), a center with expertise in cutting-edge computational and data-driven research with tangible and direct impacts on academic research, public service, and industry partners in healthcare, finance, and technology. Qualifications: BA/BS degree (MA or PhD preferred) in Computer Science, Mathematics, Engineering, Neuroscience or related technical field. One to three years of academic or professional experience. Programming experience in MATLAB is required. Additional experience in Python, C++, or LABView is preferred. Extensive background in either computational neuroscience, image analysis, computer vision, or machine learning is preferred. If interested in applying, please submit a CV along with 3 references to jerry(a)chen-lab.org<mailto:jerry@chen-lab.org>.

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Post-doc on modeling neural circuit dynamics and homeostasis
by Jochen Triesch Nov. 4, 2019

Nov. 4, 2019

A 2-year post-doc position on modeling neural circuit dynamics and homeostasis is available at the Frankfurt Institute for Advanced Studies (https://fias.uni-frankfurt.de/en/) The project aims at better understanding how different plasticity mechanisms maintain neural circuits in healthy activity regimes suitable for information processing and how these mechanisms may break down in certain network disorders. We are also interested the role of non-neuronal cell types in the process. The project is jointly lead by Prof. Jochen Triesch and Prof. Peter Jedlicka. The successful candidate will have the possibility to work closely together with experimental labs from Frankfurt’s vibrant Neuroscience community. The project is funded through Frankfurt’s new Center for Personalized Translational Epilepsy Research (CePTER). Applications (single pdf file including CV, list of publications, statement of research interests and names and email addresses of three references) should be sent to jedlicka(a)em.uni-frankfurt.de and triesch(a)fias.uni-frankfurt.de. The ideal candidate will have obtained a PhD/Master Degree in Computational Neuroscience or closely related field and have a strong interest in applying their knowledge to problems of medical relevance. A strong background in either neural mass models or spiking neural network models or compartmental modeling is expected. Experience in modeling epilepsy, neural plasticity and neuroimmune interactions is a plus. Review of applications will begin immediately and continue until the position has been filled. -- Prof. Dr. Jochen Triesch Johanna Quandt Research Professor Frankfurt Institute for Advanced Studies http://fias.uni-frankfurt.de/~triesch/ Tel: +49 (0)69 798-47531 Fax: +49 (0)69 798-47611

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Ten Years Reproducibility Challenge / ReScience special issue
by Nicolas Rougier Nov. 4, 2019

Nov. 4, 2019

Dear all, We’ve just launched the "Ten Years Reproducibility Challenge” whose goal is to try to compile & run your old code (> 10 years) that accompanied one of your published article or preprint (details below). More information at: https://github.com/ReScience/ten-years/ Deadline for submission: 01/04/2020 Nicolas Rougier --- Did you ever try to run an old code that you wrote for a scientific article you published years ago? Did you encounter any problems? Were you successful? We are curious to hear your story. This is the reason why we are editing a special issue of ReScience to collect these stories. The ten years reproducibility challenge is an invitation for researchers to try to run the code they've created for a scientific publication that was published more than ten years ago. This code can be anything (statistical analysis, numerical simulation, data processing, etc.), can be written in any language and can address any scientific domain. The only mandatory condition to enter the challenge is to have published a scientific article before 2010, in a journal or a conference with proceedings, which contains results produced by code, irrespectively of whether this code was published in some form at the time or not. Note that we do not ask you to write a new version of your old code. We ask you instead to try to make your old code to run on modern hardware/software (with minimal modifications) in order to check if you can obtain the exact same results that were publised at least ten years ago. Sounds easy? We have good reasons to think this might be more difficult than you think. And maybe the first problem you'll have to solve is to find your own source code. More information at: https://github.com/ReScience/ten-years/

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COMPUTATIONAL NEUROSCIENCE MODELER FOR PAIN PROJECT
by Hugo-Geerts＠In-Silico-Biosciences.com Nov. 3, 2019

Nov. 3, 2019

Do you want to make a difference in the life of patients suffering from chronic pain? Are you motivated to help solving the opioid epidemic? In Silico Biosciences (www.in-silico-biosciences.com) a pioneer in Quantitative Systems Pharmacology (QSP) for R&D in CNS diseases has openings for computational neuroscientists. The fully funded European Pain project (duration 3.5 years with start in early 2020) aims to develop an actionable biophysically realistic computer model of the relevant human neuronal circuits for analgesia, sedation, cognitive impairment, and substance abuse liability for opioids. These models will be integrated in an existing QSP platform for the introduction of approved therapeutic medications based on their pharmacological properties for combination therapy. The models will be developed based on preclinical knowledge combined with human neurophysiology and imaging studies of relevant neuronal circuits, will be calibrated using biomarkers and therapeutic interventions in human patients and predictions will be tested in preclinical models and in clinical studies. This is an unique opportunity to work in a world-class multi-disciplinary consortium ranging from preclinical studies over computer modeling of pharmacological interventions to clinical studies and at the same time pursuing a meaningful outcome for patients. The platform is based on NEURON software. The positions are at both post-doc and graduate student level, with the opportunity to pursue a PhD and can be embedded in the Leiden-Amsterdam Center for Drug Research in Leiden, the Netherlands. However, alternative locations and flexible remote working arrangements can be considered depending on individual circumstances. Salary is commensurate with experience. Please send your CV, covering letter and the names of two references to Hugo-Geerts(a)In-Silico-Biosciences.com

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15 funded PhD Positions in Neuroscience | IMPRS for Brain and Behavior
by Ezgi Bulca Oct. 31, 2019

Oct. 31, 2019

15 fully-funded PhD Positions in Neuroscience | IMPRS (International Max Planck Research School) for Brain and Behavior Bonn, Germany & Jupiter, Florida (USA) Looking for a PhD position in neuroscience? Apply to our fully-funded, international PhD program in the Max Planck Society! IMPRS for Brain and Behavior is a transatlantic collaboration between the Max Planck associated caesar in Bonn and the University of Bonn, along with the USA partners Max Planck Florida Institute for Neuroscience (MPFI) and Florida Atlantic University. The Projects More than 40 labs with an enormous variety of research projects are seeking outstanding PhD candidates to join their research. See our website (https://www.imprs-brain-behavior.org/research/faculty/) for further information on our faculty and possible doctoral projects. Successful candidates will work in a young and dynamic, interdisciplinary, international environment, embedded in the local scientific communities in Bonn or Jupiter. Your Profile Highly qualified and motivated aspiring PhD student from any nationality. Proven track record of academic and research excellence. Bachelor's or Master's degree (or equivalent) in life sciences, physics, mathematics, computer science, engineering, or other relevant subject. Fluency in written and spoken English. Research experience is of advantage. Our Offer Immersion in a stimulating scientific culture of interaction and international cooperation. State-of-the art facilities with novel scientific technologies and advanced infrastructure. Dedicated support and mentoring personnel. Competitive salary funded for the whole duration of studies and no tuition fees. We are committed to diversity and equal opportunity for all applicants. Application deadline: December 1, 2019 https://www.imprs-brain-behavior.org/admissions/application-info/ You will need: CV, letter of motivation, contact info for 2 referees, academic certificates and transcripts. Only online applications accepted. Short-listed candidates will be interviewed in February-March. Positions must be started within 6 months of selection. All the best, Ezgi Bulca Ezgi Bulca IMPRS for Brain & Behavior Coordinator phone +49/228/9656-318 e-mail: ezgi.bulca(a)caesar.de<mailto:ezgi.bulca@caesar.de> www.imprs-brain-behavior.mpg.de research center caesar center of advanced european studies and research an associate of the Max Planck Society Ludwig-Erhard-Allee 2 53175 Bonn, Germany www.caesar.de<http://www.caesar.de/>

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CFP: 3rd Conference of Consciousness Research Network at NYU Shanghai
by Ryota Kanai Oct. 30, 2019

Oct. 30, 2019

Conference dates and venue: April 3-5, 2020, NYU Shanghai, Rooms 1502-1505 CFP deadline: December 15, 2019 Result notification: January 31, 2020 Consciousness Research Network (CoRN <https://www.conresnet.org/>) is a network that aims at connecting researchers in the fields of philosophy, neuroscience, psychology, cognitive science, biology, and related fields to deepen our understanding of the nature of consciousness. It also seeks to facilitate collaborations on interdisplinary projects. The 1st and 2nd conferences of CoRN were held in Taipei (November 2017) and Okazaki (January 2019), and were huge successes. We would like to invite submissions of abstracts to be presented at the 3rd Meeting of CoRN to be held April 3-5 at NYU Shanghai. Please submit an abstract no longer than 300 words to the submission site <https://www.conresnet.org/abstract-submission8203.html>. Submissions will be refereed and selected as talks or posters based on quality and relevance to CoRN. If you have any questions about the conference, please contact Lu Teng at lt77(a)nyu.edu Here is a list of confirmed speakers: Tim Bayne (Monash University, Australia) Domenica Bueti (SISSA – International School for Advanced Studies, Italy) Acer Chang (Araya, Inc., Japan) Amit Chaturvedi (University of Hong Kong, Hong Kong) Juan Chen (South China Normal University, China) Tony Cheng (National Chengchi University, Taiwan) Colin Klein (Austrialian National University, Australia) Sze Chai Kwok (East China Normal University, China) Luo Liang (Beijing Normal University, China) Ying-Tung Lin (National Yang-Ming University, Taiwan) Kengo Miyazono (Hiroshima University, Japan) Pengmin Qin (South China Normal University, China) Shinsuke Shimojo (Caltech, USA) Chen Song (Cardiff University, UK) Lu Teng (NYU Shanghai, China) Xiaohong Wan (Beijing Normal University, China) Masataka Watanabe (The University of Tokyo, Japan) Makiko Yamada (QST, Japan) Xilin Zhang (South China Normal University, China) Local organizing committee: Acer Chang (Araya, Inc., Japan) Ryota Kanai (Araya, Inc., Japan) Sze Chai Kwok (East China Normal University) Lu Teng (NYU Shanghai)

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Postdoctoral positions in invasive human neurophysiology (Dr. Pouratian’s lab)
by Mahsa Malekmohammadi Oct. 30, 2019

Oct. 30, 2019

Three postdoctoral research positions are immediately available at the UCLA Neurosurgical Brain Mapping and Restoration Lab (NBMRL), under the direction of Dr. Nader Pouratian in the UCLA Department of Neurosurgery. We are seeking individuals with interest in any of the following areas: (1) pathophysiology of Parkinson disease (2) therapeutic mechanisms of deep brain stimulation (3) network basis of anesthesia and consciousness (4) biophysics of visual cortex stimulation. These NIH-funded positions are outstanding opportunities to receive training and develop innovative research projects in a highly productive and cutting-edge research program. The successful candidates are expected to be team players and collaborate closely with other team members (both within UCLA and across our collaborative multi-site network) to develop and validate data acquisitions and behavioral testing and advanced image and signal analyses and interpretation. The candidates are also expected to report, through oral presentation and written reports/papers, algorithms and experimental findings. In addition, opportunities to develop research proposals under direct mentorship from the PI will be provided. Candidates with a Ph.D. in Computational Neuroscience, Engineering, Physics, Mathematics or Data Science, an excellent research record, and a drive to work independently and collaboratively to solve conceptual and computational challenges are encouraged to apply. A strong quantitative and theoretical skillset is a must, prior experience in biomechanical modeling, cognitive sciences or neuroscience, and a background in relevant modeling and analysis of behavioral or neurophysiological data are a plus. Excellent written and oral English communication skills and proven ability to conduct high-quality research evidenced by first-author publications are required. Previous experience with human scalp-or intracranial EEG, animal intracranial electrophysiology, or advanced MRI analysis is preferred. Interested candidates should contact *Dr. Nader Pouratian* at *npouratian(a)mednet.ucla.edu <npouratian(a)mednet.ucla.edu>* and submit a letter of interest, CV, and at least 2 references. -- *Mahsa Malekmohammadi, PhD* Visiting Assistant Professor Department of Neurosurgery University of California, Los Angeles 300 Stein Plaza, Suite 562 Los Angeles, CA 90095 Email: mmalekmohammadi(a)mednet.ucla.edu Office: (310) 206-9187

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an educational review on time delay systems
by Claudius Gros Oct. 30, 2019

Oct. 30, 2019

Dear All Time delays are ubiquitous in the brain. To this regard we would like to point out a new introductory review, Chaos in time delay systems, an educational review by H. Wernecke, B. Sandor, C. Gros Physics Reports 824, 1-40 (2019). https://www.sciencedirect.com/science/article/abs/pii/S0370157319302601 abstract -------- The time needed to exchange information in the physical world induces a delay term when the respective system is modeled by differential equations. Time delays are hence ubiquitous, being furthermore likely to induce instabilities and with it various kinds of chaotic phases. Which are then the possible types of time delays, induced chaotic states, and methods suitable to characterize the resulting dynamics? This review presents an overview of the field that includes an in-depth discussion of the most important results, of the standard numerical approaches and of several novel tests for identifying chaos. Special emphasis is placed on a structured representation that is straightforward to follow. Several educational examples are included in addition as entry points to the rapidly developing field of time delay systems. table of contents ----------------- 1 Introduction 1.1 Time delays in theory and nature 1.2 Outline 1.3 States and state histories 1.4 Lyapunov exponents 1.4.1 Local Lyapunov exponents 1.4.2 Global and maximal Lyapunov exponents 1.4.3 Global Lyapunov exponents for maps 1.5 Educational example: Stability of a fixed point 1.5.1 Analytic ansatz for local Lyapunov exponents 1.5.2 Euler map 2 Types of time delay systems 2.1 Single constant time delay 2.2 Multiple constant time delays 2.3 Time-varying delay 2.4 State-dependent delay 2.5 Conservative vs. dissipative delay 2.6 Distribution of delays 2.7 Reducible time delay systems 2.8 Neutral delay systems 2.9 Networks with delay coupling 2.10 Long time delays 3 Characterizing the dynamics of time delay systems 3.1 Fixed points 3.2 Types of chaotic motion 3.2.1 Delay induced chaos 3.2.2 Partially predictable chaos 3.2.3 Weak and strong chaos 3.2.4 Intermittent and laminar chaos 3.2.5 Transient chaos 3.3 Lyapunov spectrum 3.4 Lyapunov prediction time 3.5 Phase space contraction rate 3.6 Poincaré section 3.7 The power spectrum of attractors 3.8 The dimension of attractors 3.8.1 Mori dimension 3.8.2 Kaplan-Yorke dimension 3.8.3 Fractal dimension 3.8.4 Correlation dimension 3.9 Binary tests for identifying chaos 3.9.1 Cross-distance scaling exponent 3.9.2 Gottwald-Melbourn test 3.10 Space-time interpretation of time delay systems 4 Numerical treatment 4.1 Numerical integration 4.1.1 Euler algorithm 4.1.2 Euler integration as a discrete map 4.1.3 Explicit Runge-Kutta algorithms 4.2 Lyapunov exponents 4.2.1 Maximal Lyapunov exponent from two diverging trajectories 4.2.2 Benettin’s algorithm 4.2.3 Extracting Lyapunov exponents from the Euler map 5 Conclusions ### ### Prof. Dr. Claudius Gros ### http://itp.uni-frankfurt.de/~gros ### ### Complex and Adaptive Dynamical Systems, A Primer ### A graduate-level textbook, Springer (2008/10/13/15) ### ### Mageia, das Buch der Farben ### http://www.buchderfarben.de ### ### Life for barren exoplanets: The Genesis project ### https://link.springer.com/article/10.1007/s10509-016-2911-0 ###

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Modeller’s Workshop for the Brain Dynamics Toolbox. Nov 1-22, 2019.
by Stewart Heitmann Oct. 29, 2019

Oct. 29, 2019

Modeller’s Workshop for the Brain Dynamics Toolbox Online Course Nov 1-22, 2019 The Brain Dynamics Toolbox is an open toolbox for simulating dynamical systems in neuroscience. This on-line course is for researchers, students and instructors who wish to use the toolbox to build their own dynamical models. Participants learn the art of programming differential equations in Matlab and how to use the toolbox to solve those equations interactively. Topics include programming Ordinary Differential Equations, Partial Differential Equations, Delay Differential Equations, Stochastic Differential Equations, Auxiliary Plot Functions and command-line tools. Example code is provided in all cases. Course Website https://bdtoolbox.org/p/modellers-workshop/ Important Dates Enrolments open Friday 1st Nov, 2019. Enrolments close Friday 22nd Nov, 2019. Stewart Heitmann | Computational Scientist Victor Chang Cardiac Research Institute | Lowy Packer Building | 405 Liverpool St, Darlinghurst NSW 2010 Australia E: s.heitmann(a)victorchang.edu.au | @VictorChangInst ______________________________________________________________________ The Victor Chang Cardiac Research Institute's Email is scanned by the MessageLabs Email Security System.

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