- Comp-neuro - lists.cnsorg.org

PhD-positions in computational neuroscience at the University of Oslo as part of CompSci grant in EU Horizon 2020
by Gaute Einevoll 01 Feb '21

01 Feb '21

CompSci is a Doctoral Programme launched and managed by the Faculty of Mathematics and Natural Sciences at the University of Oslo (UiO). It is partly funded by the EU Horizon 2020 under the Marie Skłodowska-Curie Action (MSCA) - Co-funding of Regional, National and International Programmes (COFUND). The CompSci Doctoral Program will recruit 32 PhDs in two calls. In this Call, we open for applications to the 1st cohort of 16 PhD fellowship positions, that will join our PhD programme starting autumn 2021 at UiO. The possible PhD-projects span over a wide range of topics where methods from computational science are applied to different fields in the natural sciences: https://www.mn.uio.no/compsci/english/projects/ Four of the possible projects in Call 1 are within computational neuroscience: * Bio-inspired neural networks for navigation<https://www.mn.uio.no/compsci/english/projects/bioscience/bio-inspired-neur…> Supervisors: Anders Malthe-Sørenssen<https://www.mn.uio.no/compsci/english/projects/supervisors/malthe-sorenssen…>, Gaute T. Einevoll<https://www.mn.uio.no/compsci/english/projects/supervisors/einevoll.html> * Large-scale recordings of neurons to reveal mechanisms of learning and memory<https://www.mn.uio.no/compsci/english/projects/bioscience/learning-and-memo…> Supervisors: Marianne Fyhn<https://www.mn.uio.no/compsci/english/projects/supervisors/fyhn.html>, Anders Malthe-Sørenssen<https://www.mn.uio.no/compsci/english/projects/supervisors/malthe-sorenssen…> * Large-scale network simulations of mouse visual cortex<https://www.mn.uio.no/compsci/english/projects/bioscience/neural-networks.h…> Supervisors: Gaute T. Einevoll<https://www.mn.uio.no/compsci/english/projects/supervisors/einevoll.html>, Marianne Fyhn<https://www.mn.uio.no/compsci/english/projects/supervisors/fyhn.html> * Modelling systems levels changes in brain aging induced by genome instability<https://www.mn.uio.no/compsci/english/projects/bioscience/brain-aging.html> Supervisors: Hilde Nilsen<https://www.mn.uio.no/compsci/english/projects/supervisors/nilsen.html>, Gaute T. Einevoll<https://www.mn.uio.no/compsci/english/projects/supervisors/einevoll.html> For information about how to apply, see https://www.jobbnorge.no/en/available-jobs/job/193610/compsci-call-1-marie-… . The extended application deadline for Call 1 is: March 1st 2021 Questions about the individual projects should be sent to the supervisors listed above. ******************************* Professor Gaute T. Einevoll Department of Physics, Norwegian University of Life Sciences, 1432 Aas, Norway; Department of Physics, University of Oslo, 0316 Oslo, Norway mobile: +47-95124536 email: Gaute.Einevoll(a)nmbu.no<mailto:Gaute.Einevoll@nmbu.no>, web: www.nmbu.no/ans/gaute.einevoll<http://www.nmbu.no/ans/gaute.einevoll>, cinpla.org<http://cinpla.org> twitter: https://twitter.com/gauteeinevoll podcast: https://vettogvitenskap.no podcast (English only): https://vettogvitenskap.no/senseandscience

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Funded Ph.D. Studentship in Computational Modelling and Machine Learning in Decision Neuroscience
by Wong-Lin, Kongfatt 01 Feb '21

01 Feb '21

Applications are invited for a funded 3-year Ph.D. studentship in Computational Modelling and Machine Learning in Decision Neuroscience at Ulster University, UK. https://www.ulster.ac.uk/doctoralcollege/find-a-phd/801216 This Ph.D. project aims to develop and apply computational techniques and modelling to understand brain and behavioural data across primate species. Specifically, the project will apply techniques in computational neuroscience, particularly biologically based neural network modelling, to elucidate the mechanisms underlying perceptual decisions abstracted from movements. The project will also use advanced machine learning methods to analyse various types of neural and behavioural data. The Ph.D. project is part of an ambitious externally funded 5-year research project proposes to break new ground by integrating data from multimodal human and non-human primate neurophysiology with computational modelling to gain convergent insights into how and where abstract decision mechanisms take place in the human and monkey brain, and provide an unprecedented, detailed view on the brain’s decision making machinery. The international collaborators are Prof. Michael Shadlen at Columbia University (USA), Prof. Stephan Bickel at Northwell-Hofstra School of Medicine (USA), Prof. Redmond O'Connell at Trinity College Dublin (Ireland), and Prof. Simon Kelly at University College Dublin (Ireland). Some relevant references: (i) O'Connell RG, Shadlen MN, Wong-Lin K, Kelly SP. Bridging Neural and Computational Viewpoints on Perceptual Decision-Making. Trends Neurosci. 2018;41(11):838‐852. doi:10.1016/j.tins.2018.06.005 (ii) Atiya NAA, Rañó I, Prasad G, Wong-Lin K. A neural circuit model of decision uncertainty and change-of-mind. Nat Commun. 2019;10(1):2287. doi:10.1038/s41467-019-10316-8 (iii) O'Connell RG, Dockree PM, Kelly SP. A supramodal accumulation-to-bound signal that determines perceptual decisions in humans. Nat Neurosci. 2012;15(12):1729‐1735. doi:10.1038/nn.3248 This timely and exciting project is available in the Computer Science Research Institute and is tenable in the Faculty of Computing, Engineering and the Built Environment at Magee Campus. The successful Ph.D. candidate will benefit from the expertise of Ulster University’s Cognitive and Computational Neuroscience, Machine Learning, and Computational Biology communities, and will interact closely with international experimental collaborators. The student will gain valuable skills and knowledge in computational and mathematical modelling, biological signal processing, machine learning, high-performance computing, mathematics/statistics, and brain sciences. All applicants should hold a first or upper second class honours degree (or equivalent) in Physics, Mathematics, Computer Science, Engineering, Statistics, Neuroscience, Biology, or a cognate area. Applications will be considered on a competitive basis with regard to the candidate’s qualifications, skills, experience, motivation and interests. Successful candidates will enrol as of 1st August 2021, on a full-time programme of research studies leading to the award of the degree of Doctor of Philosophy. The Ph.D. studentship will comprise fees together with an annual stipend and will be awarded for a period of up to three years subject to satisfactory progress. Additional financial support will be available from the supervisor's research funding for additional specialised training, research meeting and conference attendance, and computational resources. The successful student will be based at the Intelligent Systems Research Centre at Magee campus in Derry~Londonderry, with arguably the largest cluster of computational neuroscientists and neuro-inspired A.I researchers in Ireland. The city was awarded the 2013 UK City of Culture, with affordable living costs. In 2019, Ulster University was ranked 3rd in the UK for research culture and 8th in the UK for overall PhD researcher satisfaction. If you wish to discuss your proposal or receive advice on this project, please contact: Dr. KongFatt Wong-Lin, email: k.wong-lin(a)ulster.ac.uk . Apply online: https://www.ulster.ac.uk/doctoralcollege/find-a-phd/801216 The closing date for receipt of completed applications is 8th March 2021. Interviews will be held on 25th March 2021, and the starting date is on 1st August 2021. ------------------- Dr. KongFatt Wong-Lin Reader Intelligent Systems Research Centre School of Computing, Engineering and Intelligent Systems Ulster University, UK https://www.ulster.ac.uk/staff/k-wong-lin This email and any attachments are confidential and intended solely for the use of the addressee and may contain information which is covered by legal, professional or other privilege. If you have received this email in error please notify the system manager at postmaster(a)ulster.ac.uk and delete this email immediately. Any views or opinions expressed are solely those of the author and do not necessarily represent those of Ulster University. The University's computer systems may be monitored and communications carried out on them may be recorded to secure the effective operation of the system and for other lawful purposes. Ulster University does not guarantee that this email or any attachments are free from viruses or 100% secure. Unless expressly stated in the body of a separate attachment, the text of email is not intended to form a binding contract. Correspondence to and from the University may be subject to requests for disclosure by 3rd parties under relevant legislation. The Ulster University was founded by Royal Charter in 1984 and is registered with company number RC000726 and VAT registered number GB672390524.The primary contact address for Ulster University in Northern Ireland is Cromore Road, Coleraine, Co. Londonderry BT52 1SA

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Save the date: virtual INCF Assembly 19-27 April, 2021
by Helena Ledmyr 29 Jan '21

29 Jan '21

Dear INCF community, The INCF Assembly <https://neuroinformatics.incf.org/> will be a virtual meeting this year, starting on April 19. The program <https://neuroinformatics.incf.org/2021/program-at-a-glance> is currently being fine-tuned and will include: - FAIR approaches for neuroscience in general, neuroimaging, electrophysiology, and computational neuroscience - Electrophysiology, and computational neuroscience - Data science - Showcase of tools, infrastructures - Information about ongoing work in INCF councils and committees - Funders and publishers roundtable - Workshops on developing standards and a roadmap for FAIR neuroscience Abstract submission will reopen within the next couple of weeks, as will registration. If you submitted an abstract for the cancelled 2020 Assembly you will be contacted with the option to keep or retract your abstract. Registration fees are discounted for INCF members - sign up for INCF membership here <https://www.incf.org/join-incf>! We hope to see you at the INCF Assembly <https://neuroinformatics.incf.org/> ! 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

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Fully funded PhD and postdoc positions in Neuroethology / Systems Neuroscience at Max Planck Institute for Brain Research (Frankfurt, Germany)
by Stempel, Vanessa 29 Jan '21

29 Jan '21

Dear colleagues, A fully funded PhD and postdoctoral position are available in the newly installed research group “Instinctive Behaviour Circuits”, headed by Vanessa Stempel at the Max Planck Institute for Brain Research in Frankfurt, Germany. Are you excited about neuroethology and systems neuroscience? Our group works on the neural mechanisms of flexible instinctive behaviours and is looking for PhD students and postdocs to join their team! The lab will employ state-of-the-art in vivo neural activity recordings and manipulation experiments in ethologically-relevant behavioural tasks in mice, and combine these with molecular, cellular and circuit-level analyses in vitro. We're also welcoming applications for BSc and MSc research projects! Please get in touch with us via email at vanessa.stempel(a)brain.mpg.de Best, Vanessa Job ads PhD mpg.de/16351407/phd-student-instinctive-behaviour-circuits<https://www.mpg.de/16351407/phd-student-instinctive-behaviour-circuits> Postdoc mpg.de/16351421/postdoctoral-researcher-instinctive-behaviour-circuits<http://www.mpg.de/16351421/postdoctoral-researcher-instinctive-behaviour-ci…> ___________________________ DR. VANESSA STEMPEL Max Planck Research Group Leader Instinctive Behaviour Circuits Group Max Planck Institute for Brain Research Max-von-Laue-Straße 4 60438 Frankfurt am Main, Germany www.brain.mpg.de/research/instinctive-behaviour-circuits-group.html

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Simons Foundation Bridge to Independence (BTI) Award programs
by Alyssa Picchini Schaffer 28 Jan '21

28 Jan '21

The Simons Foundation is invested in supporting the next generation of researchers. Our Bridge to Independence (BTI) Award programs promote talented early-career scientists by facilitating their transition to research independence and providing grant funding at the start of their professorships. We are offering such awards through two of our programs: the Simons Collaboration on the Global Brain (SCGB), and the Simons Foundation Autism Research Initiative (SFARI). These requests for applications (RFAs) are aimed at Ph.D. and M.D. – holding scientists who are currently in training positions and intend to seek tenure-track faculty positions over the next two years (i.e., 2021-2023). Successful applicants will receive a commitment of $495,000 over three years, activated upon assumption of a tenure-track professorship. Visit bit.ly/3i3GNeA for more information on both programs. __________________________________ Alyssa Picchini Schaffer, PhD Senior Scientist & Administrative Director Neuroscience Collaborations *SIMONS FOUNDATION* 160 Fifth Avenue New York, NY 10010 646.654.0066 *main * 646.751.1277 *direct * 717.818.8281 *mobile*

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Undergraduate computational neuroscience research position
by Neymotin, Samuel (NKI) 27 Jan '21

27 Jan '21

A new Army Research Office (ARO) undergraduate research apprenticeship program (URAP) position is available for the summer of 2021 at the Nathan Kline Institute for Psychiatric Research in Orangeburg, NY (https://www.nki.rfmh.org/) Research will be conducted under the mentorship of Samuel Neymotin, Haroon Anwar, and Salvador Dura-Bernal to help achieve the goals of an ARO grant (PI: Neymotin) that aims to train neocortical circuit models to play video games using biologically-plausible learning rules, and to compare the models’ performance against commonly used deep reinforcement learning algorithms. Students will have the opportunity to learn cutting edge methods in computational neuroscience, machine learning, and Python software development, and potentially publish their results. Candidates will be considered based on their experience in computational neuroscience, machine learning, and Python programming. Candidates must be located within commuting distance to Nathan Kline Institute during the apprenticeship period. For consideration, please click the link to “Apply Now” at https://www.usaeop.com/program/undergraduate-apprenticeships/ Make sure to use code U803 (Nathan Kline Institute) and apply by the deadline (March 15, 2021). Letters of recommendation are optional. For questions, email Samuel.Neymotin(a)nki.rfmh.org<mailto:Samuel.Neymotin@nki.rfmh.org> For more information about the URAP visit: http://www.usaeop.com/<https://protect2.fireeye.com/v1/url?k=1b10bbdd-47344dbc-1b1242e8-0cc47a6d17…> ________________________________ IMPORTANT NOTICE: This e-mail is meant only for the use of the intended recipient. It may contain confidential information which is legally privileged or otherwise protected by law. If you received this e-mail in error or from someone who was not authorized to send it to you, you are strictly prohibited from reviewing, using, disseminating, distributing or copying the e-mail. PLEASE NOTIFY US IMMEDIATELY OF THE ERROR BY RETURN E-MAIL AND DELETE THIS MESSAGE FROM YOUR SYSTEM. Thank you for your cooperation.

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[jobs] machine learning research scientist at NIMH
by Francisco Pereira 27 Jan '21

27 Jan '21

### HIRING: machine learning research scientist The Machine Learning Team at the National Institute of Mental Health (NIMH) in Bethesda, MD, has an open position for a machine learning research scientist. The NIMH is the leading federal agency for research on mental disorders and neuroscience, and part of the National Institutes of Health (NIH). ### About the NIMH Machine Learning Team Our mission is to help NIMH scientists use machine learning methods to address a diverse set of research problems in clinical and cognitive psychology and neuroscience. These range from identifying biomarkers for aiding diagnoses to creating and testing models of mental processes in healthy subjects. Our overarching goal is to use machine learning to improve every aspect of the scientific effort. We work with many different data types, including very large brain imaging datasets from various imaging modalities, behavioral data, and picture and text corpora. We have excellent computational resources, both of our own (tens of high-end GPUs for deep learning, several large servers) and shared within the NIH (a cluster with hundreds of thousands of CPUs, and hundreds of GPUs). As a machine learning research group, we develop new methods and publish in the main machine learning conferences (e.g. NeurIPS and ICLR), as well as in psychology and neuroscience journals. Many of our problems require devising research approaches that combine imaging and non-imaging data, and leveraging structured knowledge resources (databases, scientific literature, etc) to generate explanations and hypotheses. You can find more about our work and publications at https://cmn.nimh.nih.gov/mlt ### About the position We are seeking candidates who are capable of combining machine learning, statistical, and domain-specific computational tools to solve practical data analysis challenges (e.g. designing experiments, generating and testing statistical hypotheses, training and interpreting predictive models, and developing novel models and methods). Additionally, candidates should be capable of visualizing and communicating findings to a broad scientific audience, as well as explaining the details of relevant methods to researchers in a variety of domains. Desirable experience that is not required, but will be considered very favorably: - neuroimaging data processing and analysis (any MRI modality, as well as MEG and EEG) - other types of neural data (e.g. neural recording, calcium imaging) - modelling of human and animal learning and decision-making - Bayesian statistical modelling Finally, you should have demonstrable experience programming in languages currently used in data-intensive, scientific computing, such as Python, MATLAB or R. Experience with handling large datasets in high performance computing settings is also very valuable. Although this position requires a Ph.D. in a STEM discipline, we will consider applicants from a variety of backgrounds, as their research experience is the most important factor. This is an ideal position for someone who wants to establish a research career in method development and applications driven by scientific and clinical needs. Given our access to a variety of collaborators and large or unique datasets, there is ample opportunity to match research interests with novel research problems. We also maintain collaborations outside of the NIH, driven by our own research interests. If you would like to be considered for this position, please send francisco.pereira(a)nih.gov a CV, with your email serving as cover letter. We especially encourage applications from women and members of underrepresented groups. If you already have a research statement, please feel free to send that as well. There is no need for reference letters at this stage. Other inquiries are also welcome. Thank you for your attention and interest! ReplyForward <https://drive.google.com/u/0/settings/storage?hl=en&utm_medium=web&utm_sour…> <https://www.google.com/intl/en/policies/terms/> <https://www.google.com/intl/en/policies/privacy/> <https://www.google.com/gmail/about/policy/>

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[CFP] ICLR 2021 Workshop on "How Can Findings About The Brain Improve AI Systems?"
by Mariya Toneva 26 Jan '21

26 Jan '21

ICLR 2021 - Workshop on "How Can Findings About The Brain Improve AI Systems?" Submission deadline: February 26, 2021 Workshop website: https://iclrbrain2ai.github.io/ Contact: brain2ai.2021(a)gmail.com The brain comprises billions of neurons organized into an intricate network of highly specialized functional areas. This biological cognitive system can efficiently process vast amounts of multi-modal data to perceive and react to its ever-changing environment. Unlike current AI systems, it does not struggle with domain adaptation, few-shot learning, or commonsense reasoning. Inspiration from neuroscience has benefited AI in the past: modern convolutional networks mimic the deep, nested information flow in visual cortex, and hippocampal replay of previous experiences has brought about experience replay in reinforcement learning. Recent work at the intersection of neuroscience and AI has made progress in directly integrating neuroscientific data with AI systems and has led to learned representations that are more robust to label corruptions, allow for better generalization in some language tasks, and provide new ways to interpret and evaluate what domain-relevant information is learned by deep neural networks. In this workshop, we aim to examine the extent to which insights about the brain can lead to better AI. We will consider the following (non-exhaustive) list of topics for contribution: - Integration of neuroscientific data at different granularities (neural recordings, neuroimaging etc.) to train AI systems - Brain-inspired inductive biases and ML architectures for AI systems - Neuroscientific data as an evaluation metric for AI systems - Mechanistic insight into cognitive functions (vision, language, decision making, attention, etc.) - Limitations of current AI systems in tasks at which humans excel (compositionality, commonsense reasoning, continual learning, few-shot learning, causality, etc.) - Cross-modality and cross-species comparisons of neuroscientific data with respect to benefits to AI - Datasets that can facilitate the transfer of neuroscientific insight to AI Submit at: https://cmt3.research.microsoft.com/BRAIN2AI2021/Submission/Index The workshop will feature a diverse set of topics led by the following invited speakers and panelists (in alphabetical order): 1. Anima Anandkumar, California Institute of Technology 2. David Cox, Harvard University 3. Kenji Doya, Okinawa Institute of Science and Technology Graduate University 4. Allyson Ettinger, University of Chicago 5. Alona Fyshe, University of Alberta 6. Jack Gallant, University of California, Berkeley 7. Andrea Martin, Max Planck Institute for Psycholinguistics 8. Kimberly Statchenfeld, DeepMind 9. Josh Tenenbaum, MIT Formatting Instructions: All submissions must be in PDF format. Submissions are limited to four content pages, including all figures and tables; additional pages containing only references are allowed. You must format your submission using the ICLR 2021 LaTeX style files. Submissions that meaningfully violate the ICLR style (e.g., by decreasing margins or font sizes) or page limits may be rejected without further review. All submissions should be anonymous. The review process is double-blind. We also welcome recently (within the last year) published papers that are within the scope of the workshop (without re-formatting). Already-published papers do not have to be anonymous. They are eligible for a spotlight session and will only have a very light review process. Virtual format: The workshop will be geared towards more dynamic and interactive discussion focused on Q&A sessions. Accepted abstracts and papers will result in, at minimum, a pre-recorded spotlight talk. All presenters will be given live virtual “coffee break” rooms during all breaks in the conference schedule to engage in small group discussions with participants. Discussions around talks will be organized in live virtual “breakout” rooms with similar topics and themes so that workshop attendees and presenters can interact in a less formal, discussion-centric setting. Important Dates: Paper submission deadline: 11:59 PM EST, Feb 26, 2021 Author notification: 11:59 PM EST, Mar 26, 2021 Camera-ready papers due: 11:59 PM EST, Apr 15, 2021 Workshop: May 8, 2021

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2 NEUROSCIENCE / DATA SCIENCE POSITIONS (Deadline: 11 Feb 2021)
by Prata, Diana 25 Jan '21

25 Jan '21

2 NEUROSCIENCE / DATA SCIENCE RESEARCH POSITIONS IN LAB AT UNIVERSITY OF LISBON (DPRATALAB.WORDPRESS.COM <http://dpratalab.wordpress.com/>) (Deadline: 11 Feb 2021) 1 RESEARCH POSITION IN BIOMEDICAL DATA SCIENCE Work plan: Statistical analysis of retrospective neuroimaging and clinical data, using artificial intelligence (machine learning) for the development and validation of diagnostic neuroimaging biomarkers, with high potential of clinical applicability; coordination with Portuguese and UK research, IT and medical teams within an academic-entrepreneurial join-venture, with the goal of helping clinical decision-making in neurodegenerative illnesses. Up to 2 years duration. Details in: http://www.eracareers.pt/opportunities/index.aspx?task=global&jobId=130697 <http://www.eracareers.pt/opportunities/index.aspx?task=global&jobId=130697> 1 RESEARCH POSITION IN HUMAN NEUROSCIENCE Work plan: Statistical analysis of varied psychophysiological data (EEG and/or MRI and/or pupillometry) and write up of scientific articles in clinical study with pharmacological intervention of oxytocin, with the goal of characterizing the role of oxytocin in human brain function in health and in psychosis. Up to 1.5 years duration. Details in: http://www.eracareers.pt/opportunities/index.aspx?task=global&jobId=130890 <http://www.eracareers.pt/opportunities/index.aspx?task=global&jobId=130890> Diana Prata, Phd Principal Investigator & Lecturer, Institute of Biophysics and Biomedical Engineering, FCUL Visiting Lecturer, IoPPN, King's College London Associate Investigator, CIS, ISCTE-IUL (+351)966595936; https://dpratalab.wordpress.com/ <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdpratalab…>, https://neurocolab.wordpress.com/ <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fneurocola…>.

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Postdoc position in multimodal imaging of brain dynamics
by Laura Lewis 25 Jan '21

25 Jan '21

Dear colleagues, We have an open postdoctoral position in multimodal imaging of brain states, please feel free to circulate the ad below. *Postdoctoral position in multimodal imaging of brain dynamics* We have an opening for a postdoctoral associate to lead multimodal neuroimaging studies of brain function in Laura Lewis' lab in the Department of Biomedical Engineering at Boston University ( http://www.lewisneurolab.org) This position offers the opportunity to develop multimodal neuroimaging and analysis techniques, and study the neural basis and cognitive consequences of sleep and arousal states. We use fast fMRI, simultaneous EEG-fMRI, computational modeling, ultra-high field (7 Tesla) imaging, and other multimodal approaches to measure and analyze brain function across diverse states. Areas of focus include: - fast fMRI/EEG studies of brain dynamics - thalamic and brainstem networks across vigilance states - neural basis of sleep and sleep deprivation - sleep and mood states in major depression - neurovascular coupling and cerebrospinal fluid physiology - sleep and brain function in aging The lab is a fast-paced and interdisciplinary environment that supports its members in achieving their long-term research and career goals, and has strong collaborations throughout the Boston-area computational neuroscience and neuroimaging communities. The position may involve conducting neuroimaging studies at both Boston University and at the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital. For more information, see http://www.lewisneurolab.org/positions . This position requires a Ph.D. in neuroscience, engineering, computer science, psychology, or related fields. To apply, please email C.V., a statement describing research experience and future interests and goals, and names of three references to Laura Lewis, ldlewis(a)bu.edu thanks, Laura Lewis Assistant Professor of Biomedical Engineering Boston University https://www.lewisneurolab.org/

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CFP 30th International Conference on Artificial Neural Networks ICANN 2021, Sept 14-17, Bratislava, SK
by Paolo Masulli ENNS 22 Jan '21

22 Jan '21

30th International Conference on Artificial Neural Networks ICANN 2021 https://e-nns.org/icann2021 Bratislava, Slovakia 14 - 17 September 2021 ============================================================= The International Conference on Artificial Neural Networks (ICANN) is the annual flagship conference of the European Neural Network Society (ENNS). In 2021 the Faculty of Mathematics, Physics and Informatics (FMPI), Comenius University in Bratislava, together with the Slovak Society for Cognitive Science, organize the 30th ICANN Conference from the 14th to the 17th of September 2021 in Bratislava, Slovakia. *Possibility of online/hybrid event:* in case the organization of a physical event will not be possible because of COVID-19 travel/gathering restrictions, the conference will happen online. * **CONFERENCE TOPICS* ICANN 2021 is a dual-track conference featuring tracks in Brain Inspired Computing and Machine Learning and Artificial Neural Networks, with strong cross-disciplinary interactions and applications. All research fields dealing with Neural Networks will be present at the conference. A non-exhaustive list of topics includes: Machine Learning: Deep Learning, Neural Network Theory, Neural Network Models, Graphical Models, Bayesian Networks, Kernel Methods, Generative Models, Information Theoretic Learning, Reinforcement Learning, Relational Learning, Dynamical Models, Recurrent Networks. Brain Inspired Computing: Cognitive models, Computational Neuroscience, Self-organisation, Reinforcement Learning, Neural Control and Planning, Hybrid Neural-Symbolic Architectures, Neural Dynamics, Cognitive Neuroscience, Brain Informatics, Perception and action. Neural Applications for: Bioinformatics, Biomedicine, Intelligent Robotics, Neurorobotics, Language Processing, Image Processing, Sensor Fusion, Pattern Recognition, Data Mining, Neural Agents, Brain-Computer Interaction, Neural Hardware, Evolutionary Neural Networks. *CALL FOR CONTRIBUTED SCIENTIFIC COMMUNICATIONS* All scientific communications presented at ICANN 2021 will be reviewed and scientifically evaluated by a panel of experts. The conference will feature two categories of communications: - oral communications (15'+5') - poster communications. *Call for Special Sessions* ICANN 2021 organizers cordially invite internationally recognised experts to organise Special sessions and workshops within the general scope of the conference. Special Session Proposal request should be sent to icann2021(a)fmph.uniba.sk *CALL FOR PAPERS* Authors willing to present original contributions in either oral or poster category may submit: - A full paper of maximum 12 pages (including references) to be published in Springer-Verlag Lecture Notes in Computer Science (LNCS) series with individual DOI. - An extended abstract of maximum 4 pages to be published in Springer-Verlag Lecture Notes in Computer Science (LNCS) series, without indexing. The number of oral slots is limited. In case the number of requested oral presentations is larger than the available slots the ICANN scientific committee will select which papers will be reassigned to a poster session. This selection will be based on the coherence of the programme and is totally independent of the category of submission. Submission of communications will be on the conference website: https://e-nns.org/icann2021/ *IMPORTANT DATES* Deadline for special sessions proposals: 1 Mar 2021 Opening of contribution submissions: 15 Feb 2021 Deadline for full paper and extended abstract submission: 15 Mar 2021 Notification of acceptance: 1 May 2021 Camera-ready paper and registration opening: 1 June 2021 Deadline for early registration at discount rate: 30 June 2021 *BEST PAPER AWARDS* ENNS will sponsor a maximum of four best paper awards. All awards will be presented during the final ceremony. *TRAVEL GRANTS* The European Neural Network Society sponsors a number of Student Travel Grants covering part of the costs for attending ICANN. Details will be provided on the conference website. *ORGANISATION* General Chairs: Igor Farkaš (FMPI, Comenius University in Bratislava, Slovakia) Ľubica Beňušková (FMPI, Comenius University in Bratislava, Slovakia) Organising Committee Chairs: Kristína Malinovská (FMPI, Comenius University in Bratislava, Slovakia), Alessandra Lintas (ENNS Lausanne, Switzerland) Honorary Chairs: Stefan Wermter, University in Hamburg, Germany (ENNS President) Věra Kůrková, Czech Academy of Sciences, Prague, Czechia (past ENNS President) Communication Chair: Paolo Masulli (Technical University of Denmark, ENNS)

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Registration Deadline is approaching!
by Mary 21 Jan '21

21 Jan '21

Dear community, As we are approaching deadline (January 30) for registering for "EEG/ERPs Recording and Analysis: A multifaceted approach to EEG signals" Online Course, here is a reminder for the interested researchers who haven’t been registered yet. The "EEG/ERPs Recording and Analysis: A multifaceted approach to EEG signals" Online Course is going to be held by Dr. Raphaël Fargier, PhD in Cognitive Neuroscience, Université Claude Bernard Lyon 1, France, who is a researcher in cognitive neuroscience with 10 years of experience and his research is focused on semantic cognition and the neurobiology of language. Through the course you will learn about the basics of EEG signal and how to record it. You will learn different approaches to EEG signal processing, that are more or less commonly adopted in cognitive neuroscience, including the study of Event-Related Potentials, Microstates/Topographic patterns, and Brain oscillations. You will learn about EEG signal preprocessing and how to compute ERPs, Microstates and Time-frequency maps in relationship with the constraints linked to experimental manipulations and designs. There will be a heavy focus on critical thinking about the choices of analyses as a function of research questions, challenges depending on experimental designs, and parameters to pay attention to. The variety and appropriateness of statistical methods currently used to validate (or not) hypotheses about cognitive processes will also be discussed. All of that will be evidenced through the presentation and discussion of case studies in electrophysiology of language. At the end of the course, you will know the strengths and weaknesses of these tools, and will be able to decide which measure is best adapted to your own scientific investigations about cognition. Prospective overview of the sessions 1. Basics of EEG signal and EEG recordings * Overview of the theory behind neural signals * Contrasting neuroimaging methods * Presentation of different EEG recording systems and their classical features * Tips on EEG recordings * Principles of experimental designs using EEG in cognitive neuroscience (events, timing etc) 2. EEG pre-processing Goal: Mastering the successive pre-processing steps including principles and challenges of: * Artifact rejection and correction (e.g. ICA; 3D Spline electrode interpolation) * Filtering (e.g. parameters, band widths etc) * Re-referencing (e.g. mastoid, average reference, Laplacian) * single-to-noise and number of trials 3. ERPs * Presentation of classical ERPs as markers of cognitive processes(e.g. N1/P2, P1, N400, etc.) * Computing single-subject and group-average ERPs: Pre-stimulus baseline correction (rationale, parameters, tips) Methods used to extract measures including amplitudes, latencies and topographies of ERPs Methods for statistical evaluation of differences across experimental manipulations * Differences between stimulus-aligned and response-aligned epochs, and associated challenges for signal processing 4. Spatio-temporal segmentation * Origin of microstates * Rationale of Spatio-temporal segmentation (StS) and presentation of successive steps of analyses (e.g. Topography consistency test, Tanova) * Presentation of two ways to compute StS (different toolboxes) and the respective parameters to take care of * Extraction of measures, and statistical evaluations of differences across experimental manipulations via fitting (e.g. global explained variance, duration, presence, etc.) * Single-trials and mixed models 5. Time-frequency analyses * Rationale of oscillatory dynamics in EEG signal (evoked vs. induced activity) * Challenges in pre-processing to obtain time-frequency maps as compared to ERPs * Different methods used for time-frequency decomposition * Challenges of baseline normalization (the case of response-aligned epochs) * The various measures that can be extracted from time-frequency maps and the variety of approaches for statistical validation You can watch the introductory webinar to this course using the linke below: https://sciencebeam.com/raphael-fargier-webinar/ For more information and registration click on the link below: https://sciencebeam.com/eeg-erps-recording-and-analyses/ Don’t miss this opportunity!

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PhD/Postdoc at the Group for Neural Theory, ENS, Paris
by CAYCO GAJIC Natasha 21 Jan '21

21 Jan '21

Dear all, A PhD or postdoctoral position is available in Alex Cayco Gajic's team in the Group Neural Theory, at the ENS, in Paris, France (http://iec-lnc.ens.fr/group-for-neural-theory/ [1]). The project will use recurrent neural networks to understand cerebello-cortical dynamics during motor learning. A component of the project can be to develop analysis tools for broader use in systems neuroscience. The Group for Neural Theory is a highly interactive and dynamic environment situated in central Paris, and embedded within the strong Parisian theoretical neuroscience community. The ideal candidate should have a strong quantitative background, e.g. in computational neuroscience, physics, applied maths, or computer science. Previous experience in neuroscience and/or machine learning is preferred but not required. Starting dates are flexible. Candidates should send a letter of motivation (2 pages max), the contact information of 2 to 3 referees and their CVs to natasha.cayco.gajic at ens.fr [2]. Please feel free to email me with any informal inquiries. Best, Alex https://sites.google.com/view/caycogajic/home Links: ------ [1] http://iec-lnc.ens.fr/group-for-neural-theory/ [2] http://ens.fr/

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postdoc and PhD position on body schema modeling @CTU Prague
by Matej Hoffmann 20 Jan '21

20 Jan '21

* Dear colleagues, there is a postdoc and PhD openingin the humanoid, cognitive, and neurorobotics group (https://cyber.felk.cvut.cz/research/groups-teams/humanoids/) coordinated by Dr. Matej Hoffmann (https://sites.google.com/site/matejhof/) at the Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague. The topics are in the context of a 5-year project entitled “Whole-body awareness for safe and natural interaction: from brains to collaborative robots” for excellence in fundamental research from the Czech Science Foundation (see https://cyber.felk.cvut.cz/news/new-gacr-expro-project <https://cyber.felk.cvut.cz/news/new-gacr-expro-project/>for more information) and include: - Analysis and modeling of infant behavioral data related to reaching, reaching to the self, and mirror self-recognition - Employing humanoid robots with artificial skin to construct embodied computational models of body and peripersonal space representations - Neural network models of multisensory integration and peripersonal space - Social human-robot interaction focusing on touch and interpersonal distance Open positions: Postdoc. The postdoc will independently conduct research and will also be involved in shaping the research of the group and supervising students. The gross salary will be in the range of CZK 50 000-70 000 per month (approx. 2000-2700 EUR) depending on qualification, plus direct bonuses for scientific achievements such as top-tier publications. PhD student. The topic will be co-defined with the student depending on his skills and interests. The standard duration of the PhD study is 4 years. The funding corresponds to a gross salary of CZK 45 000 per month (approx. 1750 EUR), plus direct bonuses for scientific achievements such as top-tier publications. Robots and infrastructure The humanoids group has at its disposal several humanoid robots (iCub, 2 Naos - 1 with whole-body sensitive skin) and collaborative or lightweight manipulators (KUKA LBR iiwa, UR10e with Airskin, Kinova Gen3). Additional infrastructure includes several robot hands (Barrett Hand BH8-282, QB Soft Hand) and grippers, a 3D Motion Capture System, impact measuring devices, etc. The group has also access to the facilities of the Research Center for Informatics such as a high-performance computational cluster. International collaborations There is a large group of international experts who have agreed to act as collaborators/advisors on the project. These include experts in - developmental psychology: Dr. Kevin O’Regan (CNRS, Paris), Prof. Jeffrey J. Lockman (Tulane University, New Orleans) - cognitive psychology and neuroscience: Prof. Matthew Longo (Birkbeck University, London), Prof. Tobias Heed (Bielefeld), Prof. Andrea Serino (University of Lausanne), Dr. Jean-Paul Noel (Center for Neural Science at New York University), Drs. M.Gori and Giulia Cappagli (Italian Institute of Technology, Dr. S. Signorini (IRCSS Fondazione Mondino Pavia) - physical human-robot interaction: Prof. Sami Haddadin (TU Munich), Dr. Arash Ajoudani (Italian Institute of Technology), Dr. Michael Zillich (Blue Danube Robotics – manufacturer of Airskin) - social human-robot interaction: Dr. Alessandra Sciutti (Italian Institute of Technology), Dr. Hagen Lehmann (University of Macerata) Prague There is currently a very lively international ecosystem in the areas of robotics and AI - at the Department and in Prague in general. See, for example, http://rci.cvut.cz/or https://prg.ai/en/. How to apply. The application should include: -Motivation letter (max. 1 page) - CV (including 2 reference persons) -1 Letter of recommendation (can be from 1 of the reference persons above) Please send the applications or inquiries to matej.hoffmann(a)fel.cvut.czwith (“PhD application” or “postdoc application” in the subject). The positions are open until filled. Best regards, Matej Hoffmann * -- Matej Hoffmann, PhD Assistant Professor Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague https://sites.google.com/site/matejhof/home +420 224 357 387

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survey for a standardized format for model exchange
by Nichol W. Killian 20 Jan '21

20 Jan '21

Hello Colleagues, We recently received funding, as part of the NSF Convergence Accelerator Program (https://www.nsf.gov/od/oia/convergence-accelerator/) for a multi-investigator project that aims to develop a standardized format for exchanging and executing computational models developed by researchers in cognitive science, neuroscience, and machine learning. As part of the project, we have constructed a brief survey to gauge the computational model usages from various domains/communities, and the value that such an exchange format would have. We would greatly appreciate it if you would take a few moments to provide us with information regarding the modeling environments you use frequently, and the benefits and/or challenges you would see for developing such an exchange format. https://docs.google.com/forms/d/e/1FAIpQLSfOZSyoWL4J_MfHTIq5Jx0dnJSVHNFH7UP… [https://lh5.googleusercontent.com/fPzuVxv5E-g2xfDpxYbODDYX68AiT6zcn5yTW4XB-…]<https://docs.google.com/forms/d/e/1FAIpQLSfOZSyoWL4J_MfHTIq5Jx0dnJSVHNFH7UP…> Computational modeling survey<https://docs.google.com/forms/d/e/1FAIpQLSfOZSyoWL4J_MfHTIq5Jx0dnJSVHNFH7UP…> docs.google.com Data from this survey will only be used for informational query and will not be shared with outside sources/marketing companies. The survey is anonymous, unless you chose to add an email address for follow-up correspondence. Please also feel free to convey the link to this survey to others (in your lab or other colleagues) who you believe could provide useful feedback. Thank you for contributing to our project and to furthering the science. - Jonathan Cohen, Princeton Neuroscience Institute Nichol Killian Research Project Coordinator Princeton Neuroscience Institute Princeton University

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Virtual Event Announcement: Symposium on Explanation in Neuroscience and Artificial Intelligence (SENAI)
by Jessica Thompson 19 Jan '21

19 Jan '21

Symposium on Explanation in Neuroscience and Artificial Intelligence (SENAI) Join us on *Wednesday February 10th, 2021* for a virtual symposium on philosophical and scientific approaches to Explanation in Neuroscience and Artificial IntelligenceSpeakers: - Ida Mommenejad, Microsoft Research - John Krakauer, Johns Hopkins University - Andrew Saxe, Oxford University - Lotem Elber-Dorozko, Hebrew University - Rosa Cao, Stanford University - Cameron Buckner, University of Houston Themes: - Reductionism & emergence - Representation & computation - Explanation & understanding Details online: https://sites.google.com/mila.quebec/senai/homeRegister for free and view the event: https://www.crowdcast.io/e/senai2021/register

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ikerbasque postdoctoral fellows: track towards permanent position
by Serafim Rodrigues 18 Jan '21

18 Jan '21

Dear all, Ikerbasque, the Basque Foundation for Science, has launched a new international call to reinforce research and scientific careers in the Basque Country. In particular it announces the following: - 20 positions for experienced postdoctoral researchers Ikerbasque Research Fellows (see link <https://calls.ikerbasque.net/?_mrMailingList=132&_mrSubscriber=65&utm_campa…> ) - 5-year contracts, during the last year the researcher can be assessed to obtain a permanent contract - PhD degree between Jan2010 - Dec2018 As leader of the Mathematical Computational and Experimental Neuroscience (MCEN) research line I would like to support candidates for these positions Potential candidates: Please send before Feb 9th 2021 the following information: - updated CV and two reference letters to: srodrigues(a)bcamath.org With kind regards Serafim -- Serafim Rodrigues Group Leader *BCAM - *Basque Center for Applied Mathematics Alameda de Mazarredo, 14 E-48009 Bilbao, Basque Country - Spain Tel. +34 946 567 842 srodrigues(a)bcamath.org | www.bcamath.org/srodrigues *(**matematika mugaz bestalde)*

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Postdoc in Neural Data Science @ Tübingen for 3 years
by Philipp Berens 18 Jan '21

18 Jan '21

Dear all, we, the “Data Science for Vision Research” group at the Institute for Ophthalmic Research at the University of Tübingen (www.berenslab.org) is offering a position for a postdoctoral researcher (100%, TV-L E13) in Neural data science for initially three years to start as soon as possible. We are looking for a motivated and enthusiastic person with a PhD in computational neuroscience, machine learning or related fields with a strong interest in applying modern machine learning approaches for deciphering the neural circuits of the retina. The ideal candidate should be interested in working on combining detailed simulations of neurons with machine learning techniques, e.g. for parameter inference, methods for processing two-photon calcium or voltage imaging data, the analysis of spatial transcriptomics data of neural tissues or related topics. Further topics of interest in the lab include machine learning techniques for analyzing single-cell transcriptomics data as well as machine learning for medical image analysis. Applications should include a CV and a motivation letter – let us know why you are excited about your previous research and how you would want to work with us. Members of underrepresented groups are particularly encouraged to apply – currently, we are a diverse team from eight different countries with a reasonable gender ratio, and we are excited to receive your application! Please send your application materials as a single pdf to philipp.berens(a)uni-tuebingen.de. The application deadline is February 15th and applications will be evaluated until the position is filled. https://jobrxiv.org/job/data-science-for-vision-research-lab-university-of-… -- Professor of Data Science for Vision Research Institute for Ophthalmic Research, University of Tübingen Cluster of Excellence "Machine Learning - New Perspectives for Science" www.berenslab.org

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Tutorial on Modeling Tools: BMTK and SONATA
by Anton Arkhipov 18 Jan '21

18 Jan '21

Dear colleagues, Please join us for an online tutorial at the Allen Institute. Tools for modeling: The Brain Modeling Toolkit and SONATA data format January 28, 2021 | 10:00-11:00am PT Please register here: https://alleninstitute.org/what-we-do/brain-science/events-training/open-fo… The Brain Modeling Toolkit is a Python-based open software package for building, simulating, and analyzing large-scale neural network models. It supports the building and simulation of models at various scales. Dai et al., PLOS Comp. Bio., 2020a<https://doi.org/10.1371/journal.pcbi.1008386> The Brain Modeling Toolkit is linked to SONATA, a standardized data format for storing networks and simulations. Dai et al., PLOS Comp. Bio., 2020b<https://doi.org/10.1371/journal.pcbi.1007696> These are the software tools we used to build, simulate, and share our multi-scale models of mouse V1, which are freely available to the community. Billeh et al., Neuron, 2020<https://doi.org/10.1016/j.neuron.2020.01.040> https://portal.brain-map.org/explore/models We are looking forward to seeing you there. Anton Arkhipov Associate Investigator T: 206.548.8414 [cidimage001.png(a)01D5B043.A5662590] www.alleninstitute.org<https://nam12.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.alleni…>

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PhD position in decision-making at University of Balearic Islands
by Catalina Vich Llompart 14 Jan '21

14 Jan '21

A 3 year PhD student position starting on March-April 2021 is offered to work with Dr. Catalina Vich at Universitat de les Illes Balears (UIB), together with Dr. Jonathan Rubin at University of Pittsburgh (UPitt), and Dr. Tim Verstynen and Dr. Eric Yttri at Carnegie Mellon University (CMU). The PhD student will be involved in an international project between USA and Spain to investigate circuit-level mechanisms of adaptive decision-making. They will engage in research on learning algorithms in spiking networks with an emphasis on cortico-basal ganglia-thalamic networks and the role of dopamine, as well as on the relation between spiking dynamics and abstract decision-making frameworks. Required skills from the PhD student: We are looking for highly motivated and self-driven candidate with strong interest and experience in computational neuroscience and significant computational expertise. To be accepted in the PhD program, a MSc degree is required preferably in mathematical biology, computational biology or related disciplines. Students who do not hold a MSc degree but hold an undergraduate degree of 300ECTS are also encouraged to apply. A high level of written and spoken English and good programming skills (python and C) are essential. The accepted candidate will be mentored, supervised and trained by C.Vich, J. Rubin and T.Verstynen, and they will have to occasionally visit the USA team (when pandemic safety restrictions are lifted). Environment The Universitat de les Illes Balears (https://www.uib.eu <https://www.uib.eu/>) is located in Mallorca, the highest island of the Balearic Islands, at the foot of the Tramuntana mountains, an area declared a World Heritage Site by the UNESCO, as well as being just a few kilometres from Mallorca’s finest beaches. It is also ranked among the top 5 Spanish universities in innovation and technological development and in research quality. The university is well connected with the main city, Palma, and other villages. It has good transport links to the whole of the archipelago. In fact, it has a bus and underground service with good timetables and frequencies. The accepted student will be a member of the group of Dynamical Systems (SSDD, http://www.ssdd.uib.es <http://www.ssdd.uib.es/>) and the institute of Applied Computing and Community Code (IAC3, http://iac3.uib.es <http://iac3.uib.es/>), with ample opportunities to interact with other young researchers in the fields of physics and mathematics in a highly interactive, dynamic, and multi-cultural environment. Salary Salary will be arranged in accordance to the University salaries for this purpose, which is around 16.000€/year (before TAX). To apply All applicants have to send their Curriculum Vitae, two letters of recommendation and an application letter expressing their interest to Dr. Catalina Vich at catalina.vich(a)uib.es <mailto:catalina.vich@uib.es> with subject “Phd position”. An interview may take place during the selection process. Documents can be written in either English, Catalan or Spanish. Applications will be accepted until the 15th of February. An objective rubric system will be used to score applications for the position, to avoid implicit bias. An online interview might be request. All qualified applicants will receive consideration for employment without regard to race, religion, sexual orientation, nationality, disability, etc. Demographic and cultural diversity will be considered in the selection of the trainee. __________________________ Dr. Catalina Vich Llompart Universitat de les Iles Balears

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Postdoc position: Modeling age-related cognitive decline in rhesus monkeys (Boston, MA)
by Christina M. Weaver 14 Jan '21

14 Jan '21

*Computational Neuroscience postdoc position: Modeling mechanisms of age-related cognitive decline in rhesus monkeys* A postdoctoral research fellowship in computational neuroscience is available immediately with the interdisciplinary research team led jointly by Dr. Jennifer Luebke (Dept of Anatomy & Neurobiology, Boston University School of Medicine, Boston MA), Dr. Christina Weaver (Dept of Mathematics, Franklin & Marshall College, Lancaster, PA), and Dr. Patrick Hof (Dept of Neuroscience, Icahn School of Medicine at Mount Sinai, New York NY). The central goal of the NIH-funded project is to characterize changes in the prefrontal cortex and visual cortex during normal aging in the rhesus monkey, to gain insight into mechanisms that contribute to age-related cognitive decline. The successful candidate will build computational models of cortical networks that incorporate age-related changes to individual neurons, and explore mechanisms of network dysfunction. The models will be constrained by our morphology, physiology, and behavior studies in rhesus monkeys, including new multiplexing data in collaboration with GE Healthcare. Our joint publications related to this project include Ibañez et al. *Front. Comput. Neurosci.* (2020), PMID 32009920; Rumbell et al., *J. Comput. Neuro*. (2016), PMID 27106692; and Amatrudo et al., *J. Neurosci.* (2012), PMID 23035077. The appointment as a Boston University School of Medicine research fellow will be for at least 1 year with possibility for extension based on performance. Applicants should have a strong background or interest in computational neuroscience and have a keen interest in interdisciplinary approaches that integrate modeling and empirical data in neuroscience research. Review of applications will begin immediately and will continue until the position is filled. Interested applicants should attach the following: - A cover letter, - A current CV, - A brief statement of current and future research interests, - The contact information of three references. Please be aware that references may be contacted anytime after receipt of your application. *Requirements:* - PhD or equivalent in computational neuroscience, applied mathematics, or a related field from an accredited institution is *required. * - Experience with NEURON compartmental modeling software and/or MATLAB scientific computing software is *required.* - Experience with differential equations-based mathematical models is *required.* - Excellent written and verbal communication skills is *required*. - Experience with conductance-based modeling of single neurons and/or excitatory-inhibitory networks is *preferred.* Please send inquiries and application materials to Dr. Christina Weaver, christina.weaver(a)fandm.edu . Christina M. Weaver, Ph.D. Department Chair, Mathematics Associate Professor Franklin & Marshall College P.O. Box 3003 Lancaster, PA 17604-3003 Email: christina.weaver(a)fandm.edu

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Funded PhD and Data scientist positions
by Abhishek Banerjee 14 Jan '21

14 Jan '21

Dear colleagues, Two funded *Ph.D. positions* are available in the newly established Adaptive Decision-making lab as a part of Neuroscience, Neurodisability and Neurological Disorders research theme, Biosciences Institute, Newcastle University, UK. The research carried out as part of th Ph.D fellowship will investigate the role of behaviourally relevant neural circuits in decision-making and its dysfunctions in neurological disorders using experimental and theoretical approaches (PNAS 2016; BRAIN 2019; bioRxiv 2020). Exciting local and international collaborations will ensure a high standard of training and mentorship. The position is funded (UK/EU rate) for up to 3.5 years and the application deadline is *6th January 2020*. Application details can be found here or by email provided below: https://www.findaphd.com/phds/project/mrc-dimen-doctoral-training-partnersh… . Additionally, the Banerjee Lab is also hiring a *Data Scientist* to be involved in projects that focus on understanding cortical computation during behaviour by combining large-scale recordings and imaging of neuronal populations. This person will be involved in analysing experimental data, developing software tools, and helping with data infrastructure. The application deadline is *31st January 2020*. Qualifications for the Data scientist position: - M.Sc. degree (or exceptional B.Sc.) in Physics, Computer Science, Mathematics, Engineering, or related technical field. - Programming experience in MATLAB is required, and additional experience in Python and LABView is preferred. - Background in computational neuroscience, image analysis, or machine learning is a plus. For informal inquiry, or if interested in applying for the Data scientist position, please submit a CV along with names of 3 referees to: Dr. Abhi Banerjee <abhi.banerjee(a)newcastle.ac.uk>. More details here: https://loop.frontiersin.org/people/11499/overview and http://neuronic.mit.edu/ Best wishes, Abhi -- Abhishek Banerjee Senior Lecturer Head, Adaptive Decision-making Lab Biosciences Institute Newcastle University United Kingdom I neuronic.mit.edu Skype: amiappu I @abhii_mit

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Post-doctoral position in Washington DC
by Rebekah Evans 13 Jan '21

13 Jan '21

Post-doctoral position in cellular and systems neuroscience The Evans Lab at Georgetown University is looking for an enthusiastic post-doctoral fellow for cellular and systems neuroscience research in an NIH BRAIN Initiative-funded position. This post-doc will use two-photon calcium imaging with simultaneous optogenetics to probe dendritic integration and circuitry of the extended basal ganglia including brainstem and dopaminergic neurons of the substantia nigra pars compacta. In addition, in vivo optogenetics and fiber photometry will be used to probe these circuits during behavior. Experience in electrophysiology and/or microscopy is a plus, but we can train a highly-motivated person on these techniques. Start date is flexible, but summer/fall 2021 would be ideal. Please see the Evans lab website: https://sites.google.com/view/evans-lab/home and contact Dr. Evans at re285(a)georgetown.edu with a letter of interest and CV. Rebekah Evans M.Ed., Ph.D. Assistant Professor Department of Neuroscience Georgetown University 3970 Reservoir Rd. NW, NRB EG31 Washington DC RebekahColemanEvans(a)gmail.com

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PhD position “Whole brain dynamics underlying flexible decision making in rodent” at Donders Centre for Neuroscience at Radboud University, the Netherlands
by Paul Tiesinga 13 Jan '21

13 Jan '21

PhD position "Whole brain dynamics underlying flexible decision making in rodent" at Donders Centre for Neuroscience at Radboud University, the Netherlands We are looking for A PhD candidate for a collaborative project in the groups of Liya Ma and Paul Tiesinga at the Donders Institute utilizing approaches from both experimental and computational neuroscience. You will study Reinforcement Learning (RL) processes in animal models using experimental and computational approaches. The experiments will establish a mathematical model for RL behaviour in mice, identify neural correlates for value-related parameters in the model using in vivo high-density electrophysiology, manipulate the neural correlates, and measure corresponding changes in RL-guided behaviour. The overall aim of the project is to investigate the neural mechanism by which value signals guide decision making. This will inform state-of-the-art deep learning approaches and shed light on novel interventions for psychiatric diseases. Guided and supported by our supervisory team, you will design and perform experiments in mice, analyse data, conduct computational modelling, and prepare manuscripts. You will also have the opportunity to write grants, peer-review journal articles, and contribute to teaching and event organization. We ask * A dedicated, reliable, detail-oriented, and well-organised team player. * Experience in animal behaviour preferred. * Experience in electrophysiology preferred. * Experience with MATLAB or Python preferred. * Good communication and writing skills in English. We are The Donders Institute for Brain, Cognition and Behaviour is a world-class interfaculty research centre that houses more than 700 researchers devoted to understanding the mechanistic underpinnings of the human mind. Research at the Donders Institute is focused around four themes: 1. Language and communication, 2. Perception, action and control, 3. Plasticity and memory, 4. Neural computation and neurotechnology. State-of-the-art research facilities are available for the broad range of neuroscience research that is being conducted at the Donders Institute. The Donders Institute has been assessed by an international evaluation committee as excellent and recognised as a 'very stimulating environment for top researchers, as well as for young talent'. The Donders Institute fosters a collaborative, multidisciplinary, supportive research environment with a diverse international staff. English is the lingua franca at the Institute. Paul Tiesinga's group aims to understand how information is processed in the brain by building computational models of the brain and developing methods to analyse signals recorded from the brain. Liya Ma's group studies how cognitive control processes are supported by cortical microcircuits and network-level long-range communications. You will be supported by the two teams' extensive expertise in high-density electrophysiology in behaving rodents, advanced data analyses and computational modelling. To help PhD candidates achieve their ambitions within and beyond academia, Radboud University provides various career training courses and coaching opportunities. Our groups are deeply committed to the professional development of doctoral candidates. PhD candidates at Radboud University receive a competitive salary with holiday pay, year-end bonus and other benefits. Their partners have access to Radboud University's Dual Career and Family Care Services. Please apply via the link in https://www.academictransfer.com/nl/296962/phd-candidate-in-neuroinformatic… before February 12th to receive full consideration. Best regards, Paul Tiesinga Professor of Neuroinformatics Donders Institute/Radboud University Nijmegen, The Netherlands

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Postdoc position in brain modelling at QIMR Berghofer, Brisbane, Australia
by Luca Cocchi 13 Jan '21

13 Jan '21

The Clinical Brain Networks Team, led by A/Prof. Luca Cocchi at QIMR Berghofer Medical Research Institute, is seeking a postdoctoral research fellow. The role is a key part of an NHMRC-funded project to model large-scale brain dynamics underpinning symptoms of obsessive-compulsive disorder (OCD). The successful candidate will develop novel models of large-scale brain dynamics, and use these to uncover brain activity causing OCD. This will entail: (i) mathematical and computational modelling of brain dynamics at the whole-brain level; (ii) constraining models against empirical neuroimaging data, both structural and functional; and (iii) developing novel analysis tools and implementing them for wide adoption. The role will also include collaboration with Dr Paula Sanz-Leon, A/Prof. James Roberts, A/Prof. Andrew Zalesky and Prof. Leonardo Fontenelle. The successful candidate will have: - A PhD in physics, mathematics, computational neuroscience, computer science, or a related field; - Experience in mathematical modelling; - Proficiency in programming (MATLAB and/or Python). - A strong track record of high-quality peer-reviewed publications. And ideally will also have experience in: - Pre-processing and analysis of neuroimaging data, including diffusion imaging and fMRI; - Modelling large-scale brain network dynamics; - Time series analysis and signal processing; and - Handling of large datasets. The position is in Brisbane, Australia, full-time for 3 years. Salary range is $82,506 to $88,522 p.a. plus super and salary packaging. When submitting an application, please include the following: letter of intent, curriculum vitae, list of publications. More details at: https://qimrberghofer.turborecruit.com.au/job/job_details.cfm?id=476191&fro… Closing date: 14 March 2021 Luca Cocchi Clinical Brain Networks Team QIMR Berghofer Medical Research Institute

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