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Open Rank Faculty Position, Department of Mathematics, City College of New York, CUNY
by Asohan Amarasingham Oct. 2, 2018

Oct. 2, 2018

Dear Colleagues, The Department of Mathematics of the City College of New York is hiring invites applications for one or more positions at the Assistant Professor, Associate Professor, or Professor levels, to start August 31, 2019. Computational neuroscience and computational biology generally are an area of particular interest for the search, and an area of focus both in the department and more broadly at City College and CUNY (see, for example, the Initiative for Theoretical Sciences at the CUNY Graduate Center). Thus researchers who focus on applications of mathematics or statistics to neuroscience are encouraged to apply. The department has strong mathematical research activities in a broad range of areas. Instructional needs are at all levels, including undergraduate service and major courses, and graduate courses both in the CCNY graduate programs and through the CUNY Graduate Center. The full announcement is below. Please feel free to contact me if you have further questions. Best regards, Asohan Amarasingham ==================================== https://www.mathjobs.org/jobs/jobs/12498 The Department of Mathematics of the City College of New York invites applications for one or more positions at the Assistant Professor, Associate Professor, or Professor levels, pending administrative approval, to start August 31, 2019. The department has strong research in a broad range of areas. Areas of greatest need and interest are for applicants with expertise in statistics, probability, and those areas of applied mathematics most relevant to computational biology and data science, but exceptional applicants from all areas of pure and applied mathematics will be considered. Instructional needs are at all levels, including undergraduate service and major courses, and graduate courses both in the CCNY graduate programs and through the CUNY Graduate Center. The City College of New York (CCNY) is part of the City University of New York (CUNY) system, with a strong tradition of excellence in science and engineering. CCNY serves a broad range of students and CUNY has an exemplary record in moving students from poverty to prosperity. CCNY serves a broad range of students and CUNY has an exemplary record in moving students from poverty to prosperity. The Department actively encourages applications from women and minority candidates. Applicants must apply electronically at http://www.mathjobs.org ALL APPLICANTS MUST APPLY VIA CUNYfirst FOR CONSIDERATION. Please apply by visiting this CUNY.jobs page<https://cuny.jobs/jobs/?q=19465> or by the following: Go to www.cuny.edu and click on "Employment" or visit Employment at CUNY<http://www2.cuny.edu/employment/> Click "Search job listings" Click on "More options to search for CUNY jobs" Search by Job Opening ID number 19465 Click on the "Apply Now" button and follow the instructions. The applicant must submit an application cover letter detailing interest in the position, a current CV, statements detailing research and teaching interests, a diversity statement reflecting the candidate's thoughts and experience on fostering inclusivity in the classroom and workplace, and arrange for four letters of reference to be submitted through mathjobs.org, with at least three addressing research and at least one addressing teaching qualifications. Review of applications begins October 15th, with applications considered until the position is filled. The City University of New York is an Affirmative Action/Equal Opportunity Employer and Educator.

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Frontiers Research Topic on Data Assimilation
by Axel Hutt Oct. 2, 2018

Oct. 2, 2018

Announcement of the Frontiers Research Topic -------------------------------------------------------------------------------------- Data Assimilation of Nonlocal Observations in Complex Systems -------------------------------------------------------------------------------------- Natural complex systems exhibit spatio-temporal dynamics on multiple scales that are difficult to predict and understand. To gain deeper insights into the system's dynamics and to be able to predict its evolution, observations of that system are analyzed which allows to derive or motivate models that fit that system. In general, one may distinguish two types of data. The so-called in-situ or local observations capture direct measurements of the system itself, such as temperature at a specific height in the atmosphere or electric potentials in biological cells. Other observations are not measured at a certain location but represent the integral of some relevant quantities manifesting the system's activity. Examples in meteorology for such nonlocal observations are satellite radiances, slant delays and radio occultation based on GPS data, or radar reflectivities. In biological systems, the non-invasive measurement techniques provide nonlocal observations, such as electro- and magnetoencephalogram or Magnetic Resonance Imaging. In addition to observations, realistic models are essential to improve the understanding of natural complex systems and to predict their dynamical evolution. To merge both models and observations, it is essential to develop techniques that optimally estimate the system activity well-adapted to a model and observed data. Data assimilation comprises a number of methods to merge diverse experimental data with an underlying model. Data assimilation optimally combines observations and a model to achieve a certain goal, such as optimal fitting of model parameters or providing optimal forecasts of the system's dynamics. Since the recent years have shown an increasing number of observation techniques capturing integrals of system activity, data assimilation of nonlocal observations becomes more and more important. The present Research Topic aims to bring together recent theoretical work in data assimilation of nonlocal observations with a strong link to specific applications. This article collection reflects the state-of-the-art in this research field. Examples of theoretical topics (as an unconstrained open list) are Kalman filters, variational assimilation techniques, regression techniques and stochastic optimization techniques. Applications may range from the parameter estimation in genetic regulatory networks over prediction of brain dynamics to weather forecast. We invite you to submit an abstract until November 30, 2018 and the manuscript until June 30, 2019. Contributions will be published as soon as they are accepted and synchronously gathered in the Research Topic volume. For more information, do not hesitate to contact us (email of Axel Hutt: digitalesbad(a)gmail.com) The organisers Lili Lei (Nanjing University) Marc Bocquet (Ecole des Ponts ParisTech) Alberto Carrassi (Nansen Environmental Remote Sensing Center) Axel Hutt (Deutscher Wetterdienst) Roland Potthast (Deutscher Wetterdienst) -- Axel Hutt Directeur de Recherche Deutscher Wetterdienst - German Meteorological Service Research and Development, Department FE 12 (Data Assimilation) Frankfurter Strasse 135, 63067 Offenbach, Germany Tel.: +49 69 8062 2750 http://www.geocities.ws/digitalbath/

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New temporal multiple kernel learning method for characterizing relating SC to connectivity dynamics and Brain state switching
by Dipanjan Oct. 2, 2018

Oct. 2, 2018

Dear all, It is my pleasure to share with you a very recent methods and data driven modelling paper from our lab on how Resting State Dynamics Meets Anatomical Structure: Temporal Multiple Kernel Learning (tMKL) Model to explore SC-dFC-FC tripartite relationship published in Neuroimage. https://www.sciencedirect.com/science/article/pii/S1053811918318597?via%3Di… The proposed model uses spectral graph theory techniques to partitions aspects of the whole-brain dynamics essentially into two parts: (i) characterizing temporal dynamics through identification of latent transient states, and (ii) linking them to the underlying structural geometry. These two aspects are captured using a novel blend of unique methods. The proposed solution does not make strong assumptions about the underlying data and is generally applicable to resting or task data for learning subject-specific state transitions and for successfully characterizing SC-dFC-FC relationship through a unifying framework. MATLAB code for the proposed method can be downloaded from: https://github.com/SriniwasGovindaSurampudi/tMKL Any comments/questions/suggestions on the method/code are of course welcome. Regards, Dipanjan

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Several Openings, New Lab. Systems Neuroscience.
by Carmen Varela Oct. 2, 2018

Oct. 2, 2018

We are looking for researchers (undergraduate to postdoc) to join a new systems neuroscience laboratory that will open in the rapidly growing Jupiter campus of Florida Atlantic University (FAU) in 2019. Under the direction of Dr. Carmen Varela, the lab will seek to discover fundamental cellular and network mechanisms that contribute to cognitive behavior, with a focus on learning and memory and on the role of the neuronal circuits formed by the thalamus https://www.thethalamus.org/ We will rely heavily on extracellular recordings in behaving rodents and quantitative analyses of cellular activity and local field potentials, in order to investigate how thalamic networks contribute to memory retrieval, problem solving, and sleep-dependent memory consolidation. If you are passionate about these topics we would love for you to join us and be part of the founding projects of the lab! *General requirements: * Outstanding interpersonal and communication skills, demonstrated initiative and dedication, ability to learn fast. Hands-on research experience in neuroscience preferred, particularly with rodent models. Knowledge of MATLAB (and/or other programming languages) and computational skills (signal processing, statistics) desirable. Candidates selected for an interview will be asked to provide contact information for two references. Start date is flexible from January 2019. *What you get: * · Research experience in behavioral and cognitive neuroscience, electrophysiology, optogenetics, fiber photometry. · Mentorship and guidance to help you achieve your scientific and training goals. The lab is located in the Jupiter campus of FAU, an expanding neuroscience hub that also holds our partners the Max Planck Florida Institute for Neuroscience and Scripps Research Institute. If interested in joining as a graduate student, there are several programs within FAU and with the Max Planck and Scripps (http://www.ibrain.fau.edu/gradneuro/program.html) Application deadlines for graduate programs in the Fall of 2018. *Interested candidates please send a CV and a brief description of research skills and interests to: carmenv(a)mit.edu <carmenv(a)mit.edu> *

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PhD opportunities at the Universities of Bath and Exeter
by Purcell, Sarah Oct. 2, 2018

Oct. 2, 2018

Dear all, The Universities of Bath and Exeter are seeking applications for PhD candidates for two biology/medicine modelling projects. Both projects will use a combination of mathematical modelling and data analysis (possibly with some data collection for interested applicants). The studentship will cover 3.5 years, with a start date of September 2019. However, this is open for EU students only. The first project will involve multi-scale modelling of skeletal muscle bioenergetics, with applications to deficits in cystic fibrosis. The student would primarily be based at the University of Exeter (with Dr. Kyle Wedgwood & Prof. Craig Williams) with secondments at the University of Bath (with Dr. James Betts). For more information, see here: http://www.exeter.ac.uk/studying/funding/award/?id=3236 The second project will investigate ion channel mutations associated with dementia. The student would primarily be based at the University of Bath (with Prof. Alain Nogaret) with secondments at the University of Exeter (with Prof. Andy Randall, Dr. Kyle Wedgwood). For full details of the project, please visit http://www.gw4biomed.ac.uk/available-projects-2/neuroscience-and-mental-hea… and select the project entitled "In-depth understanding of dementia-associated changes to neuronal signalling" Best wishes, Dr. Kyle Wedgwood MRC Research Fellow Centre for Biomedical Modelling & Analysis College of Engineering, Mathematics and Physical Sciences University of Exeter Living Systems Institute Stocker Road EX4 4QD ________________________________________________________________

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Postdoctoral Fellow in Multifactorial Brain Analysis of Amyotrophic Lateral Sclerosis
by Yasser Iturria Medina Oct. 1, 2018

Oct. 1, 2018

We are looking for a highly motivated postdoctoral student, for joining the *Neuroinformatics for Personalized Medicine* lab (NeuroPM) at the Montreal Neurological Institute (McGill University, Montreal, Canada) and the Kalra lab for Neuroimaging and ALS Research (University of Alberta, Edmonton, Canada). The postdoc will be under the supervision of Professors Yasser Iturria-Medina and Sanjay Kalra, and will be expected to collaborate with multiple associated groups. The project, for one year and potentially extendable for another year, includes the analysis of direct multifactorial brain interactions and intra-brain network spreading of aberrant effects in Amyotrophic Lateral Sclerosis. The NeuroPM lab (http://www.neuropm-lab.com/) is affiliated with the Healthy brain for Healthy Lives (HBHL) initiative (*https://www.mcgill.ca/hbhl/ <https://www.mcgill.ca/hbhl/>*), the Ludmer Center (http://ludmercentre.ca/) and the McConnell Brain Imaging Center (https://www.mcgill.ca/bic/) involving computationally intensive and interdisciplinary research on the brain. The MNI is an internationally renowned institution, characterized by the integration of research and patient care. The Kalra Lab ( http://www.ualberta.ca/ALS/research/) has the mission of improving our understanding of ALS biology through brain imaging and translational research. It is the central coordinating site for the Canadian ALS Neuroimaging Consortium (CALSNIC), a multicenter research platform for the collection of harmonized imaging and behavioural data. Interested candidates should have a solid background in brain imaging and Matlab. Experience in neurodegeneration and brain computational modeling will be an asset. Interested persons should send their CV, a cover letter stating research interests, and two reference letters. The competition will remain open until the position is filled. *Contact*: Yasser Iturria Medina, Emails: yasser.iturriamedina(a)mcgill.ca Sanjay Kalra, Email: kalra(a)ualberta.ca -- Yasser Iturria Medina, PhD. Montreal Neurological Institute, McGill University Montreal, Canada H3A 2B4, Phone # 514-398-1524 Lab: http://www.neuropm-lab.com/

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Graduate Student openings in the UCR Brain Game Center and Sensory Learning Lab
by Aaron Seitz Oct. 1, 2018

Oct. 1, 2018

Professor Aaron Seitz in the Department of Psychology at UC Riverside has several openings for graduate students. Students can work in one or both of the Perception and Learning lab and the Brain Game Center. The Perception and Learning lab conducts basic research on perception, learning and memory using a variety of approaches including advanced Psychophysics, EEG, and fMRI, and computational methodologies. The UCR Brain Game Center is a unique research unit that focuses on translational psychology and neuroscience work where we exploit the potential of consumer technologies to conduct research at large scale. This involves running hundreds to many thousands of participants on research studies designed to develop better measurements of perceptual and cognitive abilities as well as new training tools for these skills. To date we have developed numerous approaches addressing vision, hearing, working memory, executive function, and fluid intelligence. In both labs we use compu! tational modeling and machine learning as well as standard data analysis approaches. For more information on research in the Seitz labs please see http://faculty.ucr.edu/~aseitz/ and http://braingamecenter.ucr.edu. Prospective graduate students should send an email to aseitz(a)ucr.edu with their CV, and description of research interests. Successful applicants will receive funding toward their Ph.D. for at least 5 years. Please see the following websites for more information about the Psychology (https://psych.ucr.edu) or Neuroscience (http://neuro.ucr.edu) graduate programs. -Aaron ************************************************** Aaron Seitz, Ph.D. Professor of Psychology Director of UCR Brain Game Center University of California, Riverside 900 University Ave. Riverside, CA 92521 Ph: (951) 827-6422 Fax: (951) 827-3985 Email: aseitz(a)ucr.edu Web: http://faculty.ucr.edu/~aseitz/ BGC: http://braingamecenter.ucr.edu **************************************************

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Tenure-track faculty position in Computation Neuroscience at Western University, Canada
by Jorn Diedrichsen Sept. 29, 2018

Sept. 29, 2018

Supported by BrainsCAN, a $66M grant from the Canadian government (www.uwo.ca/brainscan<http://www.uwo.ca/brainscan>), Western University is expanding it’s strength in Neuroscience with a new tenure-track faculty position (Assistant or Associate Professor) in Computational Neuroscience. Successful candidates will join the Brain and Mind Institute (www.uwo.ca/bmi<http://www.uwo.ca/bmi>), one of the leading centres in cognitive Neuroscience in Canada, with a full range of ultrahigh field, research-dedicated MRI scanners (3T, 7T, 9.4T) and state-of-the-art laboratories for cognitive, behavioural, and neurophysiological testing in humans, non-human primates and rodents. The academic appointment of the candidate will be, depending on the candidate’s background, in the Department for Applied Mathematics, Statistics, or Computer Science. The deadline for the position in Computational Neuroscience is November 1st: https://brainscan.uwo.ca/work_with_us/vacancies/index.html Jörn Diedrichsen Western Research Chair Brain Mind Institute Department of Computer Science Department of Statistics Email: jdiedric(a)uwo.ca<mailto:jdiedric@uwo.ca> Tel: 1-519-661-2111 x86994

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Postdoctoral research in theoretical neuroscience
by Brent Doiron Sept. 29, 2018

Sept. 29, 2018

The Doiron group at the University of Pittsburgh is currently seeking up to three postdoctoral fellows to work on cutting edge problems in theoretical neuroscience. Research topics include 1) Large-scale collaboration on modeling diverse inhibitory circuits in mouse V1. The research will be in collaboration with the Columbia theory center (Ken Miller, Larry Abbott, Misha Tsodyks, and Liam Paninski) as well as experimental labs at Berkeley (Adesnik lab, Ji lab) , UCSF (Scanziani lab) and Caltech (Cai lab). 2) Modeling population activity in the visual system and its modulation through top-down cognitive processes. 3) Modeling the formation and stability mechanics of learning in recurrently coupled cortical networks. All projects will involve heavy collaboration with several prominent experimental groups both in Pittsburgh as well as abroad. The positions are 3 year terms (contingent upon satisfactory progress) with competitive salary and benefits packages offered by the University of Pittsburgh. The successful candidate will join the Mathematics department at the University of Pittsburgh and will have strong ties to the Center for the Neural Basis of Cognition in Pittsburgh (joint between Pitt and Carnegie Mellon University). Candidates should have a Ph.D. in computational neuroscience, mathematics, physics, or engineering and have an excellent track record of scholarship. The University of Pittsburgh is an affirmative action/equal opportunity employer and encourages applications from under-represented groups. Interested persons should send their CV, a cover letter stating research interests and career goals, and names and contact information of two references to: bdoiron(a)pitt.edu . The competition will remain open until the positions are filled. -- Professor of Mathematics Center for the Neural Basis of Cognition University of Pittsburgh 301 Thackeray Hall Pittsburgh, PA, 15260 www.math.pitt.edu/~bdoiron

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Faculty position in computational neuroscience at the University of Pittsburgh
by Brent Doiron Sept. 29, 2018

Sept. 29, 2018

Dear Computational neuroscience community The Dietrich School at the University of Pittsburgh invites applications for two tenure-track faculty positions at the Assistant Professor level in *Mathematical and Computational Life Sciences *to begin in the fall term of 2019. Successful candidates will be placed in the departments most suitable for their backgrounds and research programs from among the Departments of Mathematics, Biology, Neuroscience, Physics, and Chemistry. We seek outstanding scientists who will enhance and complement our existing strengths and who will collaborate with members of our sizable neuroscience, biology, biophysics, and biochemistry communities. One position is in *Mathematical and Computational Neuroscience. *Candidates working on the following topics are especially encouraged to apply: - Circuits and information flow in neuroscience - Neuronal and population dynamics - Synaptic mechanisms and dynamics - Neuronal membrane properties and ion channel function The other position is in *Mathematics and Theory of Biological Processes*. Candidates working on the following topics are especially encouraged to apply: - Mathematical ecology - Evolutionary theory - Cellular sensing and signal processing - Epigenetic and gene network dynamics The University of Pittsburgh is an active center for interdisciplinary research in the life sciences offering exciting opportunities for collaborations across departments as well as with our highly ranked medical school. The University is currently ranked third in the nation in total NIH funding, and the city of Pittsburgh is often voted “most livable” in the nation. These positions represent part of a vision to grow our community of researchers at the interface of mathematics, physics, chemistry and the life sciences. Successful candidates will have a Ph.D. and should demonstrate substantial research accomplishment and dedication to teaching. They will be expected to establish an extramurally funded research program, train graduate students, and actively participate in undergraduate education. *Review of applications will begin on October 23, 2018, *and will continue until the positions are filled*. *Applicants can apply online at: https://facultysearch.as.pitt.edu/apply/index/MjQy. Candidates should submit (a) a cover letter, (b) a CV, (c) a statement of research accomplishments and future plans, (d) a brief description of teaching interests, (e) a brief description of how your research, teaching or service demonstrates a commitment to diversity and inclusion, and (f) at least three letters of reference (for each reference, you will have the opportunity to input an email address through Interfolio’s Online Application system and a notification will be sent to the designated address with instructions). The positions are pending budgetary approval. The University of Pittsburgh is an Affirmative Action/Equal Opportunity Employer and values equality of opportunity, human dignity and diversity. EEO/AA/M/F/Vets/Disabled. Person to Contact: Erika Carpio 139 University Place Room 302 Pittsburgh, PA 15206 412-624-8361 -- Professor of Mathematics Center for the Neural Basis of Cognition University of Pittsburgh 301 Thackeray Hall Pittsburgh, PA, 15260 www.math.pitt.edu/~bdoiron

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job opening in neural dynamics and control
by Obermayer, Klaus, Prof. Dr. Sept. 28, 2018

Sept. 28, 2018

Dear moderator, can post our job announcement below on the neuroinformatics mailing list? Thank you very much! Best regards Klaus Obermayer ------------------------------------------------------------------------------------------------------------------------------------------------ Neural Information Processing Group @ Technische Universität Berlin Research Assistant (PhD Position) in Computational Neuroscience Brain network models: Dynamics and Control Salary grade E13 (TV-L Berliner Hochschulen) Duration: max. 4 years Starting date: January 1st, 2019 Working field: The successful candidate is supposed to work on the analysis and simulation of calibrated whole-brain networks using neuronal mass models and on the design and evaluation of novel control schemes for the stabilization of and the switching between their dynamical states. She/he will be part of the Collaborative Research Center "Control of self-organizing nonlinear systems: Theoretical methods and concepts of application" (https://www.itp.tu-berlin.de/sfb910/ sonderforschungsbereich_910/sonderforschungsbereich_910/) as well as the Bernstein Center for Computational Neuroscience Berlin (https://www.bccn-berlin.de/) The candidate is also expected to interact with clinical scientists who are interested in the non-invasive manipulation of the whole-brain dynamics using transcranial current stimulation. Requirements: Successfully completed university degree (Master, Diplom, or equivalent) in Computational Neuroscience, Computer Science, Mathematics, Physics, or related fields; in-depth knowledge in non-linear dynamics and stochastic processes; very good programming and English language skills. How to apply: Please send your application with the usual documents (CV, motivation letter, transcripts of records, certificates, and the names of two persons who can provide recommendation letters) to Prof. Dr. Obermayer, FG Neuronale Informationsverarbeitung, Sekr. MAR 5-6, Marchstr. 23, 10587 Berlin, Germany, or by e-mail to klaus.obermayer(a)tu-berlin.de. For information about the research group see https://www.ni.tu-berlin.de/ Please send copies only. Original documents will not be returned. Aplication deadline: 26. 10. 2018 Reference number: IV-570/18

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Two PhD positions in computational and cognitive neuroscience
by Alireza Soltani Sept. 28, 2018

Sept. 28, 2018

Two PhD positions are available in the Computational and Cognitive Neuroscience Lab <http://ccnl.dartmouth.edu/> of Alireza Soltani at Dartmouth College. This NIH-funded project aims to uncover circuit-level mechanisms underlying adaptive learning. The project involves computational modeling at different levels (mean-field to spiking networks) as well as analyses of behavioral, electrophysiological, and calcium imaging data in rats during dynamic learning and decision-making tasks. Applicants should have a strong quantitative background (e.g. physics, math, statistics, computational neuroscience, computer science, etc), good programming skills, genuine interest in understanding the brain, and a collaborative attitude. A background in neuroscience is desirable, but not essential. Interested applicants should submit an inquiry to Alireza Soltani (soltani(a)dartmouth.edu <mailto:soltani@darmouth.edu>), and submit their applications to Psychological and Brain Sciences Program <https://pbs.dartmouth.edu/graduate/graduate-admissions>at Dartmouth College. Alireza Soltani, Ph.D. Assistant Professor Department of Psychological and Brain Sciences Dartmouth College, NH Alireza.Soltani(a)Dartmouth.edu <mailto:Alireza.Soltani@Dartmouth.edu> http://ccnl.dartmouth.edu <http://ccnl.dartmouth.edu/> Phone: 603-646-2998 Office: Moore 356

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New ebook: Neural Information Theory
by James V Stone Sept. 27, 2018

Sept. 27, 2018

This book (published June 2018) is now available in Kindle and pdf formats: Principles of Neural Information Theory: Computational Neuroscience and Metabolic Efficiency by James V Stone. Reviews, synopsis, and table of contents can be found here: http://sebtelpress.com "To understand life, one has to understand not just the flow of energy, but also the flow of information." William Bialek, 2012. regards, Dr James V Stone Honorary Reader, Sheffield University, UK. Web: sebtelpress.com Twitter: @jgvfwstone

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EEG time-varying networks - paper & code
by Williams, Nitin J Sept. 27, 2018

Sept. 27, 2018

APOLOGIES FOR CROSS-POSTING: Dear all, I am just writing to let you know of our recent paper on a Markov Model-based method to analyse time-varying networks in EEG task-related data: https://doi.org/10.3389/fncom.2018.00076 The method combines sparse-MVAR (Multi Variate Auto Regressive) modelling to estimate networks, with Markov modelling to characterise network changes. We propose this method as complementing existing methods to analyse time-varying networks in EEG/MEG task-related data. MATLAB code for the method can be downloaded from: https://github.com/nitinwilliams/eeg_meg_analysis/tree/master/sMVAR_MM_tool… Any comments/questions on the method/code are of course welcome. Regards, Nitin

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Workshop announcement: The HBP CodeJam #9 Workshop
by Andrew Davison Sept. 27, 2018

Sept. 27, 2018

The HBP CodeJam #9 Workshop - Early-bird registration ends 30. Sept.! Grand Hotel Et Des Palmes, Palermo, Italy. Nov. 26, 2018 at 09:00 – Nov. 28, 2018 at 18:00 The goal of the CodeJam workshops is to catalyze open-source, collaborative software development in computational and systems neuroscience and neuroinformatics, by bringing together researchers, students and engineers to share ideas, present their work, and write code together. The general format of the workshops is to dedicate the mornings to invited and contributed talks, leaving the afternoons free for discussions, tutorials and code sprints. The theme of this 9th installment is "co-design": scientists, students and engineers from different disciplines collaborating to build research infrastructure for computation-based neuroscience, and to use this infrastructure to model brain circuits, behaviour and learning, develop novel bio-inspired computing systems, and help discover new drugs for neurological disorders. Topics of CodeJam#9: • Large-scale brain modelling: towards a mouse whole brain model • Cortical and subcortical microcircuit models: circuit and model workflows, simulation and analysing tools, computing resources and user interaction • Infrastructure and open data: Beyond traditional HPC, electrophysiology data formats and analysis • Visio-motor integration and hierarchical navigation planning: Integration with HBP Infrastructure (Neurorobotics platform) • Biological deep learning: Plasticity implementation on neuromorphic systems • Modelling for drug discovery and medicine Topics might change slightly, we are still finalizing the programme. Confirmed speakers (not yet complete): • Matteo Cantarelli • Oliver Schmid • Markus Diesmann • Stine Vennemo • Håkon Mørk • Armandi Romani • Genrich Ivaska • Shailesh Appukuttan • Bernd Schuller • Michael Denker • Alper Yegenoglu • Lorenzo Vannucci More information and registration details at https://neuralensemble.org/meetings/CodeJam9/ Registration fee: Early-bird registration ends on 30 September 2018 Programme Committee Luca L. Bologna (CNR), Andrew Davison (CNRS), Anna Kreshuk (U. Heidelberg), Eric Müller (U. Heidelberg), Jeff Muller (EPFL), Bernd Schuller (FZ Jülich) Organisers Luca L. Bologna (CNR), Alessia Bonafede (CNR), Martina Schmalholz (U. Heidelberg)

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Postdoctoral position in memory, sequence replay, and sleep
by Kamran Diba Sept. 26, 2018

Sept. 26, 2018

<https://sites.lsa.umich.edu/diba-lab/>The Diba Lab <https://sites.lsa.umich.edu/diba-lab/> at the University of Michigan Medical School is currently recruiting a postdoctoral candidate for a project recently funded by two NIMH (R01 and R21) grants. The project involves a collaboration with Dr. Ted Abel’s lab at the University of Iowa to investigate the Molecular, Cellular and Circuit Effects of Sleep Deprivation on Hippocampal Function. The successful candidate will perform and analyze large-scale neuronal recordings from freely-behaving, sleeping and sleep-deprived animals, along with chemogenetic manipulations, immunohistochemistry and biochemical assays. Data analysis of oscillatory and sequential neuronal firing patterns, using MATLAB, python, and other tools, is critical for this research and the prospective candidate should demonstrate quantitative and programming skills. The salary will be based on the National Research Service Award (NRSA) payscale <https://grants.nih.gov/grants/guide/notice-files/NOT-OD-18-175.html>. Our lab is housed in the Department of Anesthesiology and the Center for Consciousness Science <https://consciousness.med.umich.edu/> at Michigan Medicine. We are affiliated with the Department of Biomedical Engineering <http://bme.umich.edu/explore-research/> and the Neuroscience Graduate Program <http://neuroscience.med.umich.edu/program-0>. Collectively these programs and the University of Michigan at large provide a highly exciting and stimulating scientific environment for computational and systems neuroscience. The city of Ann Arbor is also consistently ranked <https://annarborusa.org/insights/communities/facts-rankings/> among the top places in the U.S. to live (with ready access to cultural events, sports, parks and natural beauty. Applicants should contact Kamran Diba: kdiba(a)umich.edu with a detailed C.V. or resume and a description of research background, skills, and interests. ------------- A top-ranked public university, the University of Michigan has a tradition of excellence in research, learning and teaching, sports and the arts, and more. The neuroscience community at the University of Michigan encompasses over 154 participating faculty from among 29 departments from the School of Medicine (including the Department of Anesthesiology), College of Literature Science and Arts, College of Engineering, School of Dentistry, School of Kinesiology and School of Public Health. As the longest standing neuroscience Ph.D. program in the United States the Neuroscience Graduate Program at U-Michigan has built an exceptional graduate program that features collaborative interactions among faculty and integration across individual disciplines. The program is composed of 70 to 80 graduate students (currently, 52% women, 30% under-represented minorities) and has more than 130 successful and accomplished alumni that work in academic research, industrial research and development, academic medicine and biotechnology. The NGP sponsors many activities that foster development of an active and cohesive neuroscience community on campus (e.g. Weekly Neuroscience Research Seminars, Annual Retreat, Spring Symposium, and Community Outreach).

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CFP: The OMG-Empathy Prediction Challenge
by Pablo Barros Sept. 26, 2018

Sept. 26, 2018

CALL FOR PARTICIPATION The One-Minute Gradual-Empathy Prediction (OMG-Empathy) Competition held in partnership with the IEEE International Conference on Automatic Face and Gesture Recognition 2019 in Lille, France. https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/omg_empathy.html I. Aim and Scope The ability to perceive, understand and respond to social interactions in a human-like manner is one of the most desired capabilities in artificial agents, particularly social robots. These skills are highly complex and require a focus on several different aspects of research, including affective understanding. An agent which is able to recognize, understand and, most importantly, adapt to different human affective behaviors can increase its own social capabilities by being able to interact and communicate in a natural way. Emotional expression perception and categorization are extremely popular in the affective computing community. However, the inclusion of emotions in the decision-making process of an agent is not considered in most of the research in this field. To treat emotion expressions as the final goal, although necessary, reduces the usability of such solutions in more complex scenarios. To create a general affective model to be used as a modulator for learning different cognitive tasks, such as modeling intrinsic motivation, creativity, dialog processing, grounded learning, and human-level communication, only emotion perception cannot be the pivotal focus. The integration of perception with intrinsic concepts of emotional understanding, such as a dynamic and evolving mood and affective memory, is required to model the necessary complexity of an interaction and realize adaptability in an agent's social behavior. Such models are most necessary for the development of real-world social systems, which would communicate and interact with humans in a natural way on a day-to-day basis. This could become the next goal for research on Human-Robot Interaction (HRI) and could be an essential part of the next generation of social robots. For this challenge, we designed, collected and annotated a novel corpus based on human-human interaction. This novel corpus builds on top of the experience we gathered while organizing the OMG-Emotion Recognition Challenge, making use of state-of-the-art frameworks for data collection and annotation. The One-Minute Gradual Empathy datasets (OMG-Empathy) contain multi-modal recordings of different individuals discussing predefined topics. One of them, the actor, shares a story about themselves while the other, the listener, reacts to it emotionally. We annotated each interaction based on the listener's own assessment of how they felt while the interaction was taking place. We encourage the participants to propose state-of-the-art solutions not only based on deep, recurrent and self-organizing neural networks but also traditional methods for feature representation and data processing. We also enforce that the use of contextual information, as well as personalized solutions for empathy assessment, will be extremely important for the development of competitive solutions. II. Competition Tracks We let available for the challenge a pre-defined set of training, validation and testing samples. We separate our samples based on each story: 4 stories for training, 1 for validation and 3 for testing. Each story sample is composed of 10 videos with interactions, one for each listener. Although using the same training, validation and testing data split, we propose two tracks which will measure different aspects of the self-assessed empathy: The Personalized Empathy track, where each team must predict the empathy of a specific person. We will evaluate the ability of proposed models to learn the empathic behavior of each of the subjects over a newly perceived story. We encourage the teams to develop models which take into consideration the individual behavior of each subject in the training data. The Generalized Empathy track, where the teams must predict the general behavior of all the participants over each story. We will measure the performance of the proposed models to learn a general empathic measure for each of the stories individually. We encourage the proposed models to take into consideration the aggregated behavior of all the participants for each story and to generalize this behavior in a newly perceived story. The training and validation samples will be given to the participants at the beginning of the challenge together with all the associated labels. The test set will be given to the participants without the associated labels. The team`s predictions on the test set will be used to calculate the final metrics of the challenge. III. How to Participate To participate to the challenge, please send us an email to barros @ informatik.uni-hamburg.de with the title "OMG-Empathy Team Registration". This e-mail must contain the following information: Team Name Team Members Affiliation Participating tracks We split the corpus into three subsets: training, validation and testing. The participants will receive the training and validation sets, together with the associated annotations once they subscribe to the challenge. The subscription will be done via e-mail. Each participant team must consist of 1 to 5 participants and must agree to use the data only for scientific purposes. Each team can choose to take part in one or both the tracks. After the training period is over, the testing set will be released without the associated annotations. Each team must submit, via e-mail, their final predictions as a .csv file for each video on the test set. Together with the final submission, each team must send a short 2-4 pages paper describing their solution published on Arxiv and the link for a github page to their solution. If a team fails to submit any of these items, their submission will be invalidated. Each team can submit 3 complete submissions for each track. IV. Important Dates 25th of September 2018 - Opening of the Challenge - Team registrations begin 1st of October 2018 - Training/validation data and annotation available 1st of December 2018 - Test data release 3rd of December 2018 - Final submission (Results and code) 5th of December 2018 - Final submission (Paper) 7th of December 2018 - Announcement of the winners V. Organization Pablo Barros, University of Hamburg, Germany Nikhil Churamani, University of Cambridge, United Kingdom Angelica Lim, Simon Fraser University, Canada Stefan Wermter, Hamburg University, Germany -- Dr.rer.nat. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.de https://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.html https://www.inf.uni-hamburg.de/en/inst/ab/wtm/

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Postdoc in computational neuroscience/mathematical biology
by Rubchinsky, Leonid L Sept. 26, 2018

Sept. 26, 2018

NSF-supported postdoctoral position in mathematical biology/computational neuroscience in my group in the Department of Mathematical Sciences at Indiana University-Purdue University Indianapolis (IUPUI). This position involves research in the mechanisms and properties of synchronization in neural and other living systems including collaboration with experimentalists. The position offers excellent interdisciplinary training possibilities in computational neuroscience and mathematical biology. Applicants should have (or expected to get in a near future) Ph.D. in mathematics, physics, neuroscience, biomedical engineering, computer science, or another related field. Applicants should have strong quantitative skills in dynamical modeling and data analysis and a strong interest in life sciences applications. Experience in nonlinear dynamics, computational neuroscience, and mathematical biology is a plus. Please apply via mathjobs.org at https://www.mathjobs.org/jobs/jobs/12619. Screening of applications will continue until position is filled. Please address informal inquires to Leonid Rubchinsky via e-mail: lrubchin(a)iupui.edu Leonid *********************** Leonid Rubchinsky, PhD Associate Professor Department of Mathematical Sciences, Indiana University - Purdue University, Indianapolis Stark Neurosciences Research Institute, Indiana University School of Medicine 402 N. Blackford St Indianapolis, IN 46202-3216 lrubchin(a)iupui.edu http://www.math.iupui.edu/~leo 317-274-9745 317-274-3460 (fax) ***********************

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Software Developer / Research Associate
by Stephanie Jones Sept. 24, 2018

Sept. 24, 2018

Applications are invited for a research software developer / research associate position in the lab of Dr. Stephanie Jones at Brown University in Providence, RI. The level of the hire depends on experience. Our group combines human electrophysiological recordings and computational neural modeling techniques to study the mechanisms and meaning of brain dynamics in health and disease. We collaborate extensively with animal electrophysiologists and clinicians to develop data constrained models that are translationally relevant. The software developer / research associate will work with a team of researchers at Brown, Mass General Hospital, and Yale, to help develop a new software tool for circuit level investigation of human magneto- and electro-encephalography (MEG/EEG) signals: Human Neocortical Neurosolver, HNN (https://hnn.brown.edu) <https://hnn.brown.edu)>. The goal of this software is to provide the community with a user friendly tool to develop and test hypotheses on the circuit origin of their data. The hired candidate will help support and expand HNN’s capabilities, including software development and working with researchers to apply HNN to specific neuroscience questions. Duties will also include development of tutorials, online resources, and participation in workshops aimed at training the community in the use and applicability of HNN. Candidates should have a Bachelor’s, Master’s, or PhD in computer science, neuroscience, biomedical engineering, and/or related field. Strong Python programming skills are required, and experience with neural modeling, particularly NEURON, is preferred. Familiarity with MEG/EEG analysis methods and/or non-invasive brain stimulation is also beneficial. Candidates should be able to work in a dynamic, interdisciplinary, and fun work environment. Interested candidates should send a cv and a brief description of qualifications and research interests to the Jones lab manager Dylan_S_Daniels(a)brown.edu <mailto:Dylan_S_Daniels@brown.edu>. ******************************************* Stephanie R. Jones, PhD Associate Professor Brown University Department of Neuroscience Stephanie_Jones(a)Brown.edu https://blogs.brown.edu/joneslab/ <https://blogs.brown.edu/joneslab/> Human Neocortical Neurosolver https://hnn.brown.edu <https://hnn.brown.edu/>

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Postdoctoral researchers - computational modeling, EEG, TMS
by Stephanie Jones Sept. 24, 2018

Sept. 24, 2018

Applications are invited for a postdoctoral position in the lab of Dr. Stephanie Jones at Brown University in Providence RI. Our group combines human electrophysiological recordings and computational neural modeling techniques to study the mechanisms and meaning of brain dynamics in health in disease. We collaborate extensively with animal electrophysiologists and clinicians to develop data constrained models that are translationally relevant. We are expanding our research efforts to including non-invasive brain stimulation. A postdoctoral position is available to integrate simultaneous human EEG and transcranial magnetic stimulation (TMS) in humans, with computational neural modeling developments. The postdoctoral researcher will help expand our new software tool Human Neocortical Neurosolver (https://hnn.brown.edu) <https://hnn.brown.edu)/> for circuit level interpretation of EEG/MEG signals to include TMS studies. She/he will also help with the design, implementation and analysis of our TMS/EEG experiments. Candidates should have a PhD in neuroscience, computational neuroscience, computer science, applied mathematics, biomedical engineering, and/or related field. Strong quantitative and programming skills are required. The ideal candidate would have experience in computational neuroscience methods applied to human EEG and brain stimulation data. However, experience in all areas is not required. Candidates should be able to work in a dynamic, interdisciplinary and fun work environment. Interested candidates should send a cv and a brief description of qualifications and research interests to the Jones lab manager Dylan_S_Daniels(a)brown.edu <mailto:Dylan_S_Daniels@brown.edu>. ******************************************* Stephanie R. Jones, PhD Associate Professor Brown University Department of Neuroscience Stephanie_Jones(a)Brown.edu https://blogs.brown.edu/joneslab/ <https://blogs.brown.edu/joneslab/> Human Neocortical Neurosolver https://hnn.brown.edu <https://hnn.brown.edu/>

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Workshop: High Performance Computing in Neuroscience
by Carnevale, Nicholas Sept. 24, 2018

Sept. 24, 2018

Does your research involve computationally intensive tasks such as large scale modeling or data analysis? Come to the workshop on High Performance Computing Resources for Parallel Simulations and Data Analysis: NSG and HPAC to share your experience with others who are dealing with similar challenges, and learn about resources that are currently available and/or being developed that may help accelerate your own research. This workshop will be held on Saturday, Nov. 3 from 8:30 AM to 12:30 PM at a location in downtown San Diego. Space is limited, and the registration deadline is Friday, Oct. 12, so you should act early. For the on-line registration form see https://neuron.yale.edu/neuron/static/courses/nsg2018/nsg2018.html The workshop will include a combination of short presentations and discussions. Confirmed speakers and topics include: "The Neuroscience Gateway" Amit Majumdar, Subhashini Sivagnanam, Kenneth Yoshimoto, Ted Carnevale "Research Activities at the Human Brain Project's High Performance Analytics and Computing Platform" Alexander Peyser "Human Neocortical Neurosolver: A New Modeling Platform for Cellular and Circuit Level Interpretation of EEG/MEG" Samuel A Neymotin, Dylan S Daniels, Noam Peled, Robert A McDougal, Ted Carnevale, Christopher I Moore, Michael L Hines, Matti Hamalainen, Stephanie R Jones "Towards a Complete Description of the Hippocampal Circuitry Underlying Sharp Wave-Mediated Memory Replay" Ivan Soltesz "Neuroanatomical models beyond the spatial resolution of MRI require HPC: The Big Brain and fiber tracts" Karl Zilles, Nicola Palomero-Gallagher and Katrin Amunts "The Virtual Brain: personalized large-scale brain network modeling and its applications" Viktor Jirsa

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Neuro-Inspired Computational Elements (NICE) 2019 Abstract Submission Open!
by Aimone, James Bradley Sept. 24, 2018

Sept. 24, 2018

Dear Colleagues: The call for abstracts for NICE 2019 is open for submissions at https://easychair.org/cfp/NICE2019 As with past NICE workshops, we are seeking submissions describing advances at the intersection of theoretical neuroscience, neural computing hardware and algorithms, and applications of this brain-inspired computing technology. Preference will be given to unpublished results that bridge our community. For agendas and videos of talks from past meetings, please see http://niceworkshop.org Submissions are 2 page extended abstracts, which will be reviewed to select full and short talks, as well as posters. New for NICE this year we are looking at potential options for proceedings papers, to be invited from the top submissions this year. Abstracts are due on November 15th. Registration will open in a few weeks. ---------------- NICE 2019 will be taking place during March 26-29, 2019 in Albany CNSE Campus in Albany, NY Important dates: Abstract call: September 15, 2018 Abstract submission open: September 22, 2018 Abstracts due: November 15, 2018 Selection announcement: January 15, 2019 ----------------- Hope to see you in Albany! Brad Aimone NICE Program Chair -------------------------- James Bradley Aimone, Ph.D. Principal Member of Technical Staff Data-driven and Neural Computing Department Center for Computing Research Sandia National Laboratories Phone: (505) 284-3147 Fax: (505) 844-4728 http://neuroscience.sandia.gov

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BrainScaleS, SpiNNaker and NES: EITN workshop 'Are we building the right user-level documentation?'
by Martina Reske Sept. 24, 2018

Sept. 24, 2018

Dear users of BrainScaleS, SpiNNaker and NEST, Documentation is where we provide guidance for our users to successfully navigate, understand and use our software. But how do we ensure that the documentation we provide is achieving this goal? We want to hear from you! This EITN workshop 'Are we building the right user-level documentation?' is an opportunity for users to help steer documentation in the right direction and for us to better understand the needs of our communities. Join us November 21 to November 22 in Paris, France. Registration is now open! See program details and register at https://eitnconf-211118.sciencesconf.org/ -- Dr. Martina Reske Scientific Coordinator Institute of Neuroscience and Medicine (INM-6) Computational and Systems Neuroscience & Institute for Advanced Simulation (IAS-6) Theoretical Neuroscience Jülich Research Centre and JARA Jülich, Germany Work +49.2461.611916 Work Cell +49.151.26156918 Fax +49.2461.619460 www.csn.fz-juelich.de<http://www.csn.fz-juelich.de> Office hours: TU & FR 9.00-17, WE & TH 9.00-13 ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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Assistant Professor positions at Keele University
by Peter Andras Sept. 23, 2018

Sept. 23, 2018

Two Assistant Professor (UK Lecturer) positions in Computer Science *Keele University *- Faculty of Natural Sciences - School of Computing and Mathematics *Closing date for applications: 21st October 2018* Keele University is renowned for its exciting approach to higher education, innovative research, beautiful campus, strong community spirit and excellent student experience. With a turnover in excess of £150 million, over 10,000 students and a total staff of approximately 2000, the University provides high quality teaching across a wide range of academic and vocational subjects and promotes world-class research. The University hosts the largest UK Smart Energy Network Demonstrator (SEND) with an associated Centre for Doctoral Training based in the School of Computing and Mathematics. Applications are welcome from dynamic and enthusiastic individuals committed to high quality teaching and research in any relevant field of Computer Science (e.g. software engineering, evolutionary systems, security, human-computer interaction, biological computation, machine learning, formal methods, distributed systems, smart energy, high-performance computing – but not restricted to these particular fields). Applicants will have interests that complement our existing research strengths while broadening the scope of our teaching expertise. The Assistant Professor (UK Lecturer) posts are part of continued growth and expansion of Computer Science at Keele, which presents many new opportunities for the development of synergies in both teaching and research. Candidates will be expected to develop an active research programme that both complements and extends our existing research profile in Computer Science. Candidates are also expected to develop research collaborations with colleagues at Keele and elsewhere in strategic research areas of the University, such as smart energy, AI, big data or digital health. Details of the research carried out in Computer Science at Keele can be found at: http://www.keele.ac.uk/scm/research/compsci/ The successful candidates will have a PhD in an appropriate area of Computer Science (or be very close to completion of his/her PhD) and will have a strong commitment to delivering high quality undergraduate teaching, including supervision of undergraduate and postgraduate research projects and the development and delivery of new modules. The post-holders will have the skills, enthusiasm and flexibility for teaching across a wide range of computer science topics and will also contribute to recruitment activities and administrative duties within our Computer Science programmes. Informal enquires can be made to Professor Peter Andras on 01782 733412 or p.andras(a)keele.ac.uk Keele University is committed to the principles of the Athena SWAN charter, and values equality and diversity across our workforce. We strive to ensure that our workforce is representative of broader society, and therefore, we would actively welcome applications from women for this role. Keele University values equality and diversity across our workforce and to ensuring our staff community is reflective of the diversity of our student population. In support of these commitments the University welcomes applications from individuals of Black, Asian and ethnic minority backgrounds for *all* roles. *For full post details please visit: www.keele.ac.uk/vacancies <http://www.keele.ac.uk/vacancies>* *Keele University employees wishing to apply should login to Employee Self Service and click on the 'View current vacancies' link.* *Closing date for applications: 21st October 2018* *Interviews will be held on: 16th November 2018* *Post reference: KU00000898*

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New, introductory, tutorial-based textbook
by Paul Miller Sept. 21, 2018

Sept. 21, 2018

Hi, Particularly if you teach introductory classes or mentor students with limited math/computational background, you may be interested in a new textbook "An Introductory Course in Computational Neuroscience" (http://mitpress.mit.edu/books/introductory-course-computational-neuroscience) The textbook contains numerous computer tutorials, with selected solutions, as well as over 100 codes used to simulate figures, all available online at https://github.com/primon23/Intro-Comp-Neuro or http://people.brandeis.edu/~pmiller/TEXTBOOK/ I hope you find it useful, Paul

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