- Comp-neuro - lists.cnsorg.org

Faculty position at Cold Spring Harbor Laboratory in computational neuroscience

by Benjamin Cowley

Hi all, Cold Spring Harbor Laboratory has an open search for a faculty position in computational/theoretical neuroscience. Applications are due Nov. 15, 2022. https://www.cshl.edu/about-us/careers/faculty-positions/ Here is the job description: Cold Spring Harbor Laboratory (CSHL) is seeking to fill a faculty position in the area of COMPUTATIONAL/THEORETICAL NEUROSCIENCE. Of particular interest to this search are candidates with expertise in computational and theoretical neuroscience, machine learning, and artificial intelligence. The successful candidate will have an outstanding record of research achievement and an innovative research program. They will join a highly interactive and collaborative neuroscience group working on neural circuits, neural development, neurogenetics, theoretical and computational neuroscience, artificial intelligence, synaptic function, brain disorders, rodent cognition, perception, and social behavior. Preference will be given to applicants at the Assistant Professor level, but outstanding candidates at all career stages will be considered. Cold Spring Harbor Laboratory is a world-renowned research and educational institution with programs in cancer, neuroscience, plant biology, genomics, and quantitative biology. Located on the North Shore of Long Island 30 miles from New York City, the Laboratory has a rich and successful research environment rooted in interdisciplinary collaboration as well as an innovative graduate school that attracts talented students each year. CSHL is committed to fostering a diverse work environment that values best practices in mentorship, equity, and inclusion. Successful candidates will be expected to establish productive research programs while mentoring diverse groups of students and postdocs. Applications are strongly encouraged from groups historically underrepresented in science, including women and U.S. racial/ethnic minority populations. To apply, please submit a cover letter, CV, description of research accomplishments, statement of future research plans, and a statement of diversity & mentoring to: https://cshl.peopleadmin.com/postings/20153 Position ID 03299-R; letters of reference will be requested separately. The statement of diversity & mentoring should describe a candidate’s mentoring philosophy, contributions to equity and inclusion in science, and prior training (as applicable) in mentoring, academic management/leadership, and antidiscrimination/antiracism. We will begin considering applications on a rolling basis on October 5, 2022, and applications will be considered until *November 15*. Inquiries regarding the search should be directed to: CSHLfacultyjobs(a)cshl.edu

Nov. 1, 2022

Dec 1 deadline: PhD student opening in the Developmental Cognitive Neuroscience lab (Bayet lab) at American University, Washington DC

by Laurie Bayet

Dr. Bayet (bayet(a)american.edu) assistant professor of Neuroscience at American University, is anticipating *accepting a PhD student for Fall 2023* through the Behavioral, Cognition, and Neuroscience (BCaN) program. The *application deadline is Dec 1st*, and prospective students may apply now at: https://www.american.edu/cas/neuroscience/phd/requirements.cfm (GRE optional). Applicants should mention the name(s) of the faculty they are interested in working with within their statement of purpose. The program provides 4 years of funding. Dr. Bayet directs the *Developmental Cognitive Neuroscience lab at American University*, which focuses on *infant cognitive development and high-level vision* research. Current projects in the lab combine electro-encephalography (EEG), eye-tracking, behavioral methods, and/or computational (e.g., machine learning) tools to uncover how infants and young children represent and understand complex visual objects, with particular focus on those visual objects that are relevant to affective, social communication (e.g., facial movements). Dr. Bayet's work has been recognized with a Rising Star award from the Association for Psychological Science (APS), and a Distinguished Early Career Contribution Award from the International Congress of Infant Studies. Learn more at: https://www.american.edu/cas/faculty/bayet.cfm and https://www.bayetlab.com/ The PhD student will have the opportunity to *contribute to ongoing* *NSF-funded research* in collaboration with Drs. Alexis Black (UBC), Lauren Emberson (UBC), and Richard N. Aslin (Haskins/Yale). The project, entitled “*Grounding computational models of vision with infant brain data*”, uses EEG and multivariate “decoding” to characterize infants' neural representations of visual objects, compare them to those of artificial neural networks, and assess relationships between language and visual representations (NSF award # 2122961 <https://www.nsf.gov/awardsearch/showAward?AWD_ID=2122961>). The Developmental Cognitive Neuroscience Laboratory is part of the Neuroscience Department (https://www.american.edu/cas/neuroscience/ ) and the Center for Neuroscience and Behavior ( https://www.american.edu/cas/center-neuroscience/ ) at American University. American University provides a stimulating intellectual environment, just 2 miles from downtown Washington DC. DC offers a vibrant research community, and American University enjoys proximity to other notable research institutions such as the National Institutes of Health. With extensive public transit, an exciting cultural and restaurant scene, many museums and public parks, and proximity to other green spaces in the surrounding region (e.g., Appalachian trail, Shenandoah National Park), Washington DC consistently ranks amongst the top US metropolitan areas for quality of life. Prior experience with developmental/neuroimaging research or programming/machine learning (we use Python, Matlab, and/or R) are preferred but not required, as training will be provided. Interested applicants may contact Dr. Bayet at bayet(a)american.edu for any inquiry. Selected recent lab publications: Ashton, K., Zinszer, B. D., Cichy, R. M., Nelson III, C. A., Aslin, R. N., & Bayet, L. (2022). Time-resolved multivariate pattern analysis of infant EEG data: A practical tutorial. *Developmental cognitive neuroscience*, *54*, 101094. https://doi.org/10.1016/j.dcn.2022.101094 Bayet, L. (2022). How infants learn from a world of faces: Implications for racial biases and mask-wearing. *Policy Insights from the Behavioral and Brain Sciences*, 9(1), 65-72. https://doi.org/10.1177/23727322211068007 Bayet, L., Perdue, K. L., Behrendt, H. F., Richards, J. E., Westerlund, A., Cataldo, J. K., & Nelson III, C. A. (2021). Neural responses to happy, fearful and angry faces of varying identities in 5-and 7-month-old infants. *Developmental cognitive neuroscience*, 47, 100882. https://doi.org/10.1016/j.dcn.2020.100882 Bayet, L., Zinszer, B. D., Reilly, E., Cataldo, J. K., Pruitt, Z., Cichy, R. M., ... & Aslin, R. N. (2020). Temporal dynamics of visual representations in the infant brain. *Developmental cognitive neuroscience* , *45*, 100860. https://doi.org/10.1016/j.dcn.2020.100860 -- Laurie Bayet, PhD (hear name <https://namedrop.io/lauriebayet>) Assistant Professor of Neuroscience, American University (202) 885-1719

Nov. 1, 2022

Postdoc position in modelling the effects of neuromodulation on balanced networks

by Fleur Zeldenrust

We are looking for a postdoctoral researcher to work on the Vidi project 'Top-down neuromodulation and bottom-up network computation, a computational study' and *study the effects of neuromodulators in balanced networks*. You will use cellular and behavioural data on the effects of dopamine, acetylcholine and serotonin in mouse barrel cortex gathered by our department over the past five years, to bridge the gap between single cell, network and behavioural effects. You will use the balanced network framework to study network activity under neuromodulation. In order to do this, you will develop a balanced network description of the barrel cortex, with realistic barrel cortex properties (see https://doi.org/10.1007/s12021-022-09576-5) Next, you will incorporate the cellular effects of dopamine, acetylcholine and serotonin that we have measured over the previous years (see https://doi.org/10.1093/gigascience/giy147 and https://doi.org/10.1101/2022.01.12.476007) into the network, and investigate their effects on overall network activity and behaviour. More particularly, through simulations and analytical derivations, you will research the effects of neuromodulators on the stability of the balanced state, synchrony, regularity and chaos. You will build on the single cell data, models and analysis methods available in our group, and your results will be incorporated into our group's further research to develop and validate machine learning and efficient coding models of (somatosensory) perception. We are therefore looking for a team player who can work well with our other group members and is willing to both learn from them and share their knowledge. *Profile* - You hold a PhD in computational neuroscience, mathematics, physics, computer science, AI or a related discipline. - Preferably, you have experience in working with balanced networks and can perform both network simulations and analytical derivations such as mean field approximations and chaos descriptions. - You are a highly motivated, independent, critical, and creative researcher who wants to bridge the gap between real data and abstract theoretical models. - You are a team player, ready to collaborate in a multidisciplinary research group. - You have an excellent command of spoken and written English. - You have experience in coding (Python and/or Matlab). *We are* You will be appointed at the Biophysics of Neural Computation group <https://www.ru.nl/donders/research/theme-4-neural-computation-neurotechnolo…> , Donders Center for Neuroscience <https://www.ru.nl/science/dcn/>, Donders Institute for Brain, Cognition and Behaviour <https://www.ru.nl/donders/>., at the Radboud University. <http://www.ru.nl/> This vibrant and multidisciplinary institute studies the organisation and function of neural circuits across scales and techniques, from genes and proteins to behaviour and from in vitro and in vivo experiments to computational modelling. It provides an open and international environment, where young scientists from different backgrounds share a fascination for the interaction between brain structure and function. For postdoctoral researchers, there is a lively community <https://www.ru.nl/donders/talent-education/postdoctoral-researchers/> and specialised support. *We offer* It concerns an employment for 0.8 - 1.0 FTE. - The gross monthly salary amounts to a minimum of €2,960 and a maximum of €4,670 based on a 38-hour working week, depending on previous education and number of years of relevant work experience (salary scale 10). - You will receive 8% holiday allowance and 8.3% end-of-year bonus. - It concerns a temporary employment for 26 months. - You will be able to use our Dual Career and Family Care Services. Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment and help your family settle in Nijmegen. - Working for us means getting extra days off. In case of full-time employment, you can choose between 30 or 41 days of annual leave instead of the legally allotted 20. *Practical information and applying* You can apply until 1 December 2022, exclusively on the website below. Kindly address your application to Fleur Zeldenrust. Please fill in the application form and attach the following documents: - A letter of motivation (max. 2 pages). - Your CV including a publication list. - A copy of a first-authored publication. - Contact details of two academic referees. The first round of interviews will take place on Thursday 8 December. You would preferably begin employment on 1 January 2023. See also: https://www.ru.nl/en/working-at/job-opportunities/postdoctoral-researcher-i… -- Fleur Zeldenrust Assistant Professor Donders Institute for Brain, Cognition and Behaviour Donders Centre for Neuroscience Faculty of Science, Radboud University Heyendaalseweg 135, room HG 00.111 6525 AJ Nijmegen, the Netherlands tel +31 24 36 53195 fleurzeldenrust.nl *Due to my own family/work balance, you may receive emails from me outside of normal working hours. I do not expect a response from you outside of your own working pattern, nor do I expect an immediate response when you are working.*

Nov. 1, 2022

Python Package: Kuramoto model

by Fabrizio Damicelli

Dear Computational Neuroscience Community, I would like to point you to a potentially useful Python Package that might be of interest for your research, especially in the realm dynamical models and synchronization phenomena. The Kuramoto model is used to study a wide range of systems (for a review on its usage in the Neuroscience, see Breakspear et al. 2010, Generative models of cortical oscillations: neurobiological implications of the Kuramoto model) "kuramoto": Python implementation of the Kuramoto model. * Code Repository: https://github.com/fabridamicelli/kuramoto * Easy install with `pip install kuramoto` * Example notebooks: https://github.com/fabridamicelli/kuramoto/tree/master/examples * A super concise intro to the model and its behaviour and further references can be found here: https://github.com/fabridamicelli/kuramoto#kuramoto-model-101 As of today, a few people already trust it and the package registers >10K total downloads, ~500/month (pypi.org) Check it out and any feedback/suggestions/bug reports are more than welcome (simply open an issue: https://github.com/fabridamicelli/kuramoto/issues) All the best, Fabrizio Damicelli

Nov. 1, 2022

Fully funded Phd position in the intersection of neuroscience and AI

by Guozhang Chen

We (the group of Prof. Wolfgang Maass) accept applications for a fully funded Phd position for research in the intersection of neuroscience and AI. This Phd student will work with our team on reverse engineering data-based models for cortical microcircuits and their learning capabilities, as for example in --Analysis of visual processing capabilities and neural coding strategies of a detailed model for laminar cortical microcircuits in mouse V1 (G. Chen, F. Scherr, W. Maass).Science Advances (Nov. 2, 2022), https://www.biorxiv.org/content/10.1101/2021.12.07.471653v3?versioned=t <https://www.biorxiv.org/content/10.1101/2021.12.07.471653v3?versioned=t> --A solution to the learning dilemma for recurrent networks of spiking neurons (Bellec, G., Scherr, F., Subramoney, A., Hajek, E., Salaj, D., Legenstein, R., & Maass, W.) Nature Communications 2020, 11(1), 1-15. In addition, the Phd student will work on the development of brain-inspired architectures and algorithms for AI, like in --Local prediction-learning enables neural networks to plan (C. Stoeckl, W.Maass) https://www.biorxiv.org/content/10.1101/2022.10.17.512572v1 <https://www.biorxiv.org/content/10.1101/2022.10.17.512572v1>, and for highly energy-efficient neuromorphic hardware, as in --A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware (A Rao, P Plank, A Wild, W Maass), Nature Machine Intelligence 4 (5), 467-479. https://igi-web.tugraz.at/PDF/261.pdf <https://igi-web.tugraz.at/PDF/261.pdf> In order to qualify for this Phd-position you need to have a master degree in computer science or related areas, very good skills in mathematics/theory, and programming experience for GPUs. You should also have an excellent record,demonstrations of your research potential, and be strongly motivated to collaborate with us on understanding “how the brain works”. If you qualify, please send me your CV, transcripts, names of referees, as well as links to your master thesis, papers, and other pertinent documents to email:<maass(a)igi.tugraz.at> Guozhang Chen on behalf of Prof. Dr. Wolfgang Maass Institut fuer Grundlagen der Informationsverarbeitung Technische Universitaet Graz Inffeldgasse 16b , A-8010 Graz, Austria http://www.igi.tugraz.at/maass/Welcome.html <http://www.igi.tugraz.at/maass/Welcome.html>

Oct. 30, 2022

Faculty position in computational neuroscience/machine learning at Stony Brook University

by Giancarlo La Camera

Stony Brook University is currently running a faculty search for a computational neuroscientist. The position will be in the Department of Neurobiology and Behavior and will be filled at the Assistant or Associate Professor level. A competitive recruitment package will include state-funded salary and benefits, newly renovated lab space and competitive start-up funding. The ideal candidate is an outstanding scientist in theoretical neuroscience, neuro-AI or in statistics/machine learning approaches to investigate topical questions in neuroscience. Candidates from diverse and underrepresented backgrounds are especially encouraged to apply. The successful candidate will join a vibrant, collaborative and diverse group of neuroscientists at Stony Brook University and its affiliated institutions, and will actively contribute to the Department’s mission in research as well as undergraduate, graduate and medical student education. Applications should be submitted at the following URL: https://apply.interfolio.com/111422. Review of applications will begin by Nov 15th, 2022 and continue until the position is filled. -- Giancarlo La Camera <https://www.stonybrook.edu/commcms/neurobiology/people/faculty_Giancarlo_La…>, PhD Associate Professor of Neurobiology and Behavior Stony Brook University

Oct. 29, 2022

PhD program in Systems/Computational/Cognitive neuroscience at U of Oregon

by Luca Mazzucato

We are accepting applications to the Interdepartmental Neuroscience Graduate Program (INGP) <https://ion.uoregon.edu/training-programs/graduate-fellows> at the Institute of Neuroscience, a robust graduate training in Neuroscience across departments at the University of Oregon. The goal of INGP is to train students to think independently, creatively, and critically about problems in neuroscience. We aim to train students in a variety of skills that will prepare students for successful research, teaching, policy, or industry career. Students can enter INGP through the departments of biology, human physiology, psychology, mathematics, physics, computer and information science, and the Knight Campus, depending on their interests. The majority of our students enter through the department of biology, which allows students to complete three rotations during their first year, in order to help students identify a laboratory in which to do their dissertation research. Students who enter through psychology, physiology, and mathematics begin in their dissertation labs immediately. Regardless of how students enter INGP, they are provided with a set of mentors at the peer and faculty levels. All graduate students are required to teach for at least one academic year during their graduate career; at least a portion of this teaching takes place the first year. *Training Program* Students typically fall into a defined training program, however, training can be tailored to fit a student’s need and research interest. We offer two training tracks: Systems, Cognitive and Theoretical - Courses: cellular neuroscience, systems neuroscience, cognitive neuroscience, computational neuroscience, combinatorics, stochastic processes, neural networks. - Journal clubs: systems neuroscience, theoretical neuroscience. - Meetings: neural circuits and behavior, zebrafish groupie, joint theory lab meetings.

Oct. 28, 2022

Doctoral studies in Computational/Theoretical Neuroscience at NYU

by Eero Simoncelli

New York University is home to a thriving interdisciplinary community of researchers using computational and theoretical approaches in neuroscience. We are interested in exceptional PhD candidates with strong quantitative training (e.g., physics, mathematics, engineering) coupled with a clear interest in scientific study of the brain. A listing of faculty, sorted by their primary departmental affiliation, is given below. Doctoral programs are flexible, allowing students to pursue research across departmental boundaries. Nevertheless, admissions are handled separately by each department, and students interested in pursuing graduate studies should submit an application to the program that best fits their goals and interests. Center for Neural Science (CNS), Graduate School of Arts & Sciences (deadline: 1 December) [https://neuroscience.nyu.edu/program.html, and https://as.nyu.edu/cns/DoctoralProgram.html] * SueYeon Chung - NeuroAI and geometry. * Andre A. Fenton - Molecular, neural, behavioral, and computational aspects of memory. * Paul W. Glimcher - Decision-making in humans and animals. Neuroeconomics. * David Heeger (also in Psychology) - Computational neuroscience, vision, attention. * Roozbeh Kiani - Vision and decision-making. * Wei Ji Ma (also in Psychology) - Perception, working memory, and decision-making. * Tony Movshon - Vision and visual development. * Bijan Pesaran - Neuronal dynamics and decision-making. * Alex Reyes - Functional interactions of neurons in a network. * John Rinzel (also in Mathematics) - Biophysical mechanisms and theory of neural computation. * Cristina Savin (also in the Center for Data Science) - Computational models of learning and memory, machine learning. * Robert Shapley - Visual physiology and perception. * Eero Simoncelli - Computational vision and audition. * Xiao-Jing Wang - Computational neuroscience, decision-making and working memory, neural circuits. * Alex Williams - Statistical analysis of neural data. Neuroscience Institute, School of Medicine (deadline: 1 December) [https://neuroscience.nyu.edu/program.html, and https://med.nyu.edu/departments-institutes/neuroscience/] * Gyorgy Buzsaki - Rhythms in neural networks. * Dmitri Chklovskii (also in the Simons Foundation) - Neural computation and connectomics. * Biyu He - Large-scale brain dynamics underlying human cognition. * Dmitry Rinberg - Sensory information processing in the behaving animal. * Shy Shoham - Methods for controlling, imaging, and analyzing neural systems. * Mario Svirsky - Auditory neural prostheses; experimental/computational studies of speech production/perception. Psychology, Cognition & Perception program (deadline: 1 December) [http://as.nyu.edu/psychology/graduate/phd-cognition-perception.html] * Todd Gureckis - Memory, learning, and decision processes. * Brenden Lake (also in the Center for Data Science) - Computational modeling of cognition, deep learning. * Michael Landy - Computational approaches to vision. * Laurence Maloney - Mathematical approaches to psychology and neuroscience. * Denis Pelli - Visual object recognition. * Jonathan Winawer - Visual perception and memory. Mathematics (deadline: 18 December) [https://gsas.nyu.edu/admissions/arc/programs/mathematics.html] * David McLaughlin - Nonlinear wave equations, computational visual neuroscience. * Aaditya Rangan - Computational neurobiology, numerical analysis. * Charles Peskin - Mathematical biology. * Daniel Tranchina - Information processing in the retina. * Lai-Sang Young - Dynamical systems, statistical physics, computational modeling and theoretical neuroscience. Data Science (deadline: 12 December) [https://cds.nyu.edu/phd-program/] * Joan Bruna (also in Computer Science) - Machine learning, signal/image processing. * Kyungyun Cho (also in Computer Science) - Machine learning, natural language processing. * Carlos Fernandez-Granda (also in Mathematics) - Optimization methods for medical imaging, neuroscience, computer vision. * Grace Lindsay (also in Psychology) - Machine learning models of the brain/mind. * Mengye Ren (also in Computer Science) - Machine learning, computer vision, representation learning. Physics (deadline: 30 December) [https://as.nyu.edu/physics/programs/graduate.html] * Marc Gershow - Perception, decision-making, and learning in neural circuits. Computer Science (deadline: 12 December) [http://www.cs.nyu.edu/home/phd/] * Davi Geiger - Computational vision and learning. * Yann LeCun - Machine learning, computer vision, robotics, computational neuroscience. Economics (deadline: 18 December) [https://as.nyu.edu/econ/graduate/phd.html] * Andrew Caplin - Economic theory, neurobiology of decision. * Andrew Schotter - Experimental economics, game theory, neurobiology of decision.

Oct. 28, 2022

EPFL - Faculty position at the intersection of computational and life sciences

by Mathis Alexander

Dear colleagues, The Schools of Computer and Communication Sciences (IC) and Life Sciences (SV) at EPFL invite applications for a faculty position at the intersection of computational and life sciences. We seek candidates who use machine learning and/or other original computational approaches to solve challenges in life sciences. The appointment could be either at the assistant professor or tenured level. Candidates must have an outstanding academic record, a compelling vision, demonstrated impact, and a strong commitment to excellence in teaching and mentoring students. EPFL attracts top students from all over the world and offers competitive salaries, generous research funding and excellent research infrastructure. Switzerland has an exceptionally high human development index and consistently ranks highly in quality of life, economic competitiveness, and innovation. Applicants must submit a cover letter, a curriculum vitae including a publication list, brief statements of research and teaching interests, and contact information of at least 3 references (5 for tenured positions) who are ready to supply a letter upon request. To apply, go to: https://facultyrecruiting.epfl.ch/position/40599570 Screening will start on December 1, 2022, but applications submitted after this date will also be considered. Questions can be addressed to: Profs. George Candea and Matteo Dal Peraro Co-chairs of the Faculty Recruiting Committee E-mail: recruiting.icsv(a)epfl.ch<mailto:recruiting.icsv@epfl.ch> For more information on our schools, please visit https://sv.epfl.c<https://sv.epfl.ch/>h<https://sv.epfl.ch/> and https://ic.epfl.ch<https://ic.epfl.ch/> EPFL is an equal opportunity employer and family-friendly university. It is committed to increasing the diversity of its faculty. It strongly encourages women to apply.

Oct. 26, 2022

EPFL AI4Science Postdoctoral Fellowship: Deadline Oct 31st.

by Mathis Alexander

Dear colleagues, The EPFL AI4Science Fellowship gives outstanding and highly motivated young researchers the chance to collaborate with a broad range of EPFL faculty on accelerating the use and furthering the understanding of machine learning methods in the scientific discovery process. The Fellowship focuses on excellence and interdisciplinarity. Therefore fellows will work with several laboratories at EPFL and will be granted ample freedom to develop their own research agenda. We expect fellows to contribute to a vibrant and multidisciplinary community of researchers passionate about the transformation of science with new data-driven methods. Initial appointments will be made for one year, with the expectation of renewal for at least a second year, upon agreement of the AI4Science scientific committee. The salary follows the generous scale for EPFL post-doctoral researchers. Starting date is flexible. Application deadline: October 31st 2022 More details are available at https://www.epfl.ch/research/domains/cis/epfl-ai4science/call-for-fellows/ Best wishes, Alexander Mathis [cid:clip_image001.png] Alexander Mathis Tenure Track Assistant Professor people/alexander.mathis mathislab.org<http://mathislab.org>

Oct. 26, 2022