- Comp-neuro - lists.cnsorg.org

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

Neuroscience Gateway (NSG) Virtual workshop as a part of Society for Neuroscience Annual meeting, San Diego Nov 2022

by Majumdar, Amitava

Hello, We are happy to announce that the Neuroscience Gateway (NSG) will host a Virtual workshop as a part of the Society for Neuroscience Annual Meeting in San Diego, November 2022. Date and time of the virtual NSG workshop: November 12, 8:30 AM - 12:30 PM USA Pacific Time Zone. We have distinguished speakers who are early career researchers to senior researchers. They will present their work, many of which utilize NSG or are neuroscience software projects and are available on NSG for neuroscientists to use on high performance computing resources. Registration is free but required by November 9th. Please register if you plan to attend. Title of the virtual workshop: Neuroscience Gateway - Enabling Large Scale Modeling, Data Processing and Dissemination of Software Details about the list of speakers, abstract of talks and registration are available here: http://www.nsgportal.org/NSG_HPAC_SfN2022_Wkshop.web.htm Thank you. Regards. NSG Team

Oct. 26, 2022

Faculty positions at Washington University in St Louis

by Geoffrey Goodhill

Electrical & Systems Engineering: Tenure-Track Faculty Positions Washington University in St Louis https://apply.interfolio.com/114838 The Electrical and Systems Engineering department at Washington University in St. Louis invites applications for multiple tenure-track faculty positions with an effective start date on or after July 1, 2023. Candidates should have earned a Ph.D. or equivalent degree in electrical engineering, systems engineering, computer engineering or a closely related discipline. Washington University is a highly-selective national research university with a strong tradition of research excellence. The University’s strategic plan, released in 2022, seeks growth of top-tier research, scholarship, and creative practice with an emphasis on transdisciplinary and cross-school research. Included in this plan are foci related to applications in medicine, public health, infrastructure, and addressing pressing societal challenges. Accordingly, we seek both junior and senior applicants who will contribute to research efforts across ESE, including in several emphasis areas: information and decision systems, including autonomous systems and human-machine interaction network science, including social systems and large-scale data analysis imaging science, including signal processing and computational imaging engineering brain science, including theory, models and methods for brain-inspired computation and for measuring and manipulating neural circuits quantum sensing and imaging, including science and technology for detection and estimation beyond classical physics. Candidates interested in this area are encouraged to note University-wide growth in quantum technology at https://quantumleaps.wustl.edu/. Candidates may apply to the quantum cluster search in addition to the ESE search. Equity, diversity and inclusion are core values at Washington University, and candidates will need to demonstrate the ability to create inclusive classrooms and environments in which a diverse array of students can learn and thrive. Candidates who will contribute to the diversity of the department are strongly encouraged to apply. Successful applicants will have a primary appointment in the department of Electrical and Systems Engineering (ese.wustl.edu) with the possibility of joint appointments in other departments. The faculty member will be expected to teach undergraduate and graduate courses in electrical and systems engineering, participate in university service, and establish a thriving externally-funded research program. Faculty positions are open for all levels. Applications should include: (1) a cover letter that identifies the candidate’s three most significant publications and describes their interest in the position; (2) a curriculum vitae; (3) a research plan for the next five years that should not exceed three pages, and should highlight the problem(s) or set of questions to be investigated, the envisioned approach, a mentoring strategy, and the proposed funding sources; (4) a statement of teaching interests and philosophy; (5) a statement describing contributions to and future plans for enhancing equity, diversity and inclusion; and (6) a list of at least three references to (https://apply.interfolio.com/114838) Priority will be given to completed applications (including submitted reference letters) received before December 15, 2022. However, applications will be accepted at any time and will be considered until the positions are filled. Professor Geoffrey J Goodhill Departments of Neuroscience, Developmental Biology, Biomedical Engineering, Computer Science and Engineering, and Electrical and Systems Engineering Washington University in St Louis St. Louis, MO 63110 g.goodhill(a)wustl.edu https://neuroscience.wustl.edu/people/geoffrey-goodhill-phd

Oct. 26, 2022

Postdoc positions at Harvard

by Cengiz Pehlevan

Dear colleagues, I want to point to a few postdoctoral fellow positions at Harvard for candidates in computational/theoretical neuroscience: 1. The George F. Carrier Postdoctoral Fellowship: https://academicpositions.harvard.edu/postings/11642 <https://academicpositions.harvard.edu/postings/11642> 2. Postdoctoral Fellow in Theoretical Neuroscience and/or Theory of Neural Computation: https://academicpositions.harvard.edu/postings/11671 <https://academicpositions.harvard.edu/postings/11671> 3. The Harvard Data Science Postdoctoral Fellows: https://datascience.harvard.edu/data-science-postdoctoral-fellows <https://datascience.harvard.edu/data-science-postdoctoral-fellows> 4. Postdoctoral fellow in the Foundations of Machine Learning: https://academicpositions.harvard.edu/postings/11762 <https://academicpositions.harvard.edu/postings/11762> Please feel free to write to me with questions. Best wishes, Cengiz

Oct. 25, 2022

INCF/OCNS SoftwareWG Dev session: Denis Alevi: Brian2CUDA: November 3, 2022, 1600 UTC over Zoom

by Ankur Sinha

Dear all, Please join us for our next dev session on Brian2CUDA: https://ocns.github.io/SoftwareWG/2022/10/18/dev-session-denis-alevi-brian2… Denis Alevi will introduce the Brian2CUDA tool in this session, and discuss its development. We will also have a discussion on GPU based simulation in neuroscience after the presentation. - Date: Thursday, November 3, 2022, 1600 UTC (Click here to see your local time: https://www.timeanddate.com/worldclock/fixedtime.html?msg=Dev+session%3A+De…) - Location (Zoom, login required): https://ucl.zoom.us/j/95692778384?pwd=VldIQ3hPTU1zczNpYjQxSSt4Z25xdz09 The abstract for the talk is below: Graphics processing units (GPUs) are widely available and have been used with great success to accelerate scientific computing in the last decade. These advances, however, are often not available to researchers interested in simulating spiking neural networks, but lacking the technical knowledge to write the necessary low-level code. Writing low-level code is not necessary when using the popular Brian simulator, which provides a framework to generate efficient CPU code from high-level model definitions in Python. Here, we present Brian2CUDA, an open-source software that extends the Brian simulator with a GPU backend. Our implementation generates efficient code for the numerical integration of neuronal states and for the propagation of synaptic events on GPUs, making use of their massively parallel arithmetic capabilities. We benchmark the performance improvements of our software for several model types and find that it can accelerate simulations by up to three orders of magnitude compared to Brian’s CPU backend. Currently, Brian2CUDA is the only package that supports Brian’s full feature set on GPUs, including arbitrary neuron and synapse models, plasticity rules, and heterogeneous delays. When comparing its performance with Brian2GeNN, another GPU-based backend for the Brian simulator with fewer features, we find that Brian2CUDA gives comparable speedups, while being typically slower for small and faster for large networks. By combining the flexibility of the Brian simulator with the simulation speed of GPUs, Brian2CUDA enables researchers to efficiently simulate spiking neural networks with minimal effort and thereby makes the advancements of GPU computing available to a larger audience of neuroscientists. References: - Publication: Brian2CUDA: flexible and efficient simulation of spiking neural network models on GPUs: https://www.frontiersin.org/articles/10.3389/fninf.2022.883700/abstract - Documentation: https://brian2cuda.readthedocs.io/en/latest/ - Source code: https://github.com/brian-team/brian2cuda We hope to see you there. On behalf of the INCF/OCNS Software working group, -- Thanks, Regards, Ankur Sinha (He / Him / His) | https://ankursinha.in Research Fellow at the Silver Lab, University College London | http://silverlab.org/ Free/Open source community volunteer at the NeuroFedora project | https://neuro.fedoraproject.org Time zone: Europe/London

Oct. 25, 2022

Upcoming Faculty Opening in Theoretical Neuroscience

by Lin, I-Chun

The Gatsby Computational Neuroscience Unit intends to recruit one Principal Investigator in Theoretical Neuroscience at any academic rank (UCL grades 8 to 10; Lecturer/Group Leader-level to Professorial). We seek candidates who focus on the mathematical underpinnings of adaptive intelligent behaviour in animals or develop mathematical tools and models to understand how neural circuits and systems function. We are particularly interested in researchers who are well placed to take advantage of collaborations within the unit; with our sister institute, the Sainsbury Wellcome Centre for Neural Circuits and Behaviour; and elsewhere at UCL. Gatsby faculty members pursue and develop their own lines of research within the broad remit of the unit’s focus on the mathematical principles of learning, perception and action in brains and machines. For an overview of our current work, please see www.ucl.ac.uk/gatsby/research-0<http://www.ucl.ac.uk/gatsby/research-0>. We maintain a singular and cohesive research culture, emphasising interaction and collaboration both within the unit and beyond. Our faculty members teach and supervise at graduate level, primarily as part of the unit’s international PhD programme. We encourage informal enquiries about this upcoming position. Interest from women and those from an ethnic minority background is particularly welcome, as they are under-represented within UCL at these levels. Please direct enquiries to I-Chun Lin (Scientific Programme Manager, i.lin at ucl.ac.uk). We will be best placed to respond to enquiries that include a short CV and a brief sketch of research interests. www.ucl.ac.uk/gatsby/vacancies<http://www.ucl.ac.uk/gatsby/vacancies> -- I-Chun Lin, PhD Scientific Programme Manager Gatsby Computational Neuroscience Unit, UCL www.ucl.ac.uk/gatsby<http://www.ucl.ac.uk/gatsby> | @GatsbyUCL<https://twitter.com/GatsbyUCL>

Oct. 25, 2022

Three 3-year positions in teaching (general AI) in Groningen, NL

by Herbert Jaeger

The AI Department in the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence (https://www.rug.nl/research/bernoulli/) at the University of Groningen (https://www.rug.nl/) offers three 3-year positions for teaching in general AI, with competitive salaries, in a most welcoming and high-ranked working environment (top-100 university, https://www.rug.nl/about-ug/profile/facts-and-figures/position-internationa…) The application deadline is November 7, 2022. Formal prerequisites are a PhD degree; outstanding holders of a MSc degree will also be considered. Details can be found at https://www.rug.nl/about-ug/work-with-us/job-opportunities/?details=00347-0… - Herbert Jaeger -- Dr. Herbert Jaeger Professor of Computing in Cognitive Materials Rijksuniversiteit Groningen Faculty of Science and Engineering - CogniGron Bernoulliborg Nijenborgh 9, 9747 AG Groningen office: Bernoulliborg 402 phone: +31 (0) 631 921588 COVID home office phone: +49 (0) 4209 930403 web: www.ai.rug.nl/minds/

Oct. 24, 2022

PhD openings in computational neuroscience, cognitive science, and Mixed Reality

by Sergio Solinas

The Theoretical and Computational Neuroscience Laboratory of Paolo Enrico and Sergio Solinas invites applications for a *Doctoral Student* position at UNISS, University of Sassari, ITALY SARDINIA. Research questions span a range of topics in theoretical/computational neuroscience, cognitive science, EEG recordings involving data analysis, brain function theory, neural network simulations using NEURON or NEST and neural activity visualization using mixed reality approaches. This research project is inscribed within the EBRAINS-ITALY PNRR funding schema for Research Infrastructures. Candidates with backgrounds in one or more than one of the following fields are welcome to apply: mathematics, statistics, artificial intelligence, physics, computer science, engineering, biology, and psychology. Experience with data analysis, proficiency with numerical methods, and familiarity with neuroscience topics and mathematical and statistical methods are desirable. Equally desirable is a curiosity about brain function, a spirit of intellectual adventure, a good social attitude, and sharing and reuse of knowledge. The application will open soon. *Please write to both enrico(a)uniss.it <enrico(a)uniss.it> & smgsolinas(a)uniss.it <smgsolinas(a)uniss.it> for details and updates.* If you wish to apply, please send the following information in one single PDF: 1. a short letter of motivation; 2. statement of research interests, limited to two pages; 3. curriculum vitæ. In all email correspondence, please include the mention “APPLICATION-PHD” in the subject header. The University of Sassari <https://en.uniss.it/> was funded in 1562 and is an active research <https://en.uniss.it/research/research-centres> institution. The city of Sassari <http://turismosassari.it/en/explore/sassari-curiosities/item/535-sassari-on…>a located in the north of Sardinia <https://www.sardegnaturismo.it/en>. The climate <https://weatherspark.com/y/58783/Average-Weather-in-Sassari-Italy-Year-Round> is among the best you can find in Europe. The life cost is relatively cheap if compared to Italy's mainland. The island of Sardinia has national and international connection flights from its three airports: Alghero <https://www.aeroportodialghero.it/>, Olbia <https://www.geasar.it/>, and Cagliari <http://www.sogaer.it/it>.

Oct. 24, 2022

Python Package: SER 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 spreading dynamics on networks. "ser": S(usceptible)E(xcited)R(efractory) model on graphs, a dynamical model of spreading excitations. Code Repository: https://github.com/fabridamicelli/ser As of today, a few people already trust it and the package registers >11K total downloads, ~500/month (pypi.org) and has been used already in a few research projects. A few interesting features: - It is light-weight and fast (`numba` accelerated), i.e. many experiments can be simply run on a laptop - Installation and getting started is easy: `pip install ser` - Example notebooks: https://github.com/fabridamicelli/ser/blob/main/examples The SER model is a classical cellular automaton model used to study all sorts of complex systems, ranging from forest fire dynamics to self-organized criticality in the brain. Despite of the simplicity of its setup, it is capable of generating complex emergent dynamics with absolutely non-trivial higher-order statistical properties. To learn more about the SER model and its applications, you might want to check out these references: - Messe et al. (2018). Toward a theory of coactivation patterns in excitable neural networks. doi.org/10.1371/journal.pcbi.1006084 - Haimovici et al. (2013). Brain Organization into Resting State Networks Emerges at Criticality on a Model of the Human Connectome. doi.org/10.1103/PhysRevLett.110.178101 - Damicelli et al. (2019). Topological reinforcement as a principle of modularity emergence in brain networks. doi.org/10.1162/netn_a_00085 Check it out and any feedback/suggestions/bug reports are more than welcome (simply open an issue: https://github.com/fabridamicelli/ser/issues) All the best, Fabrizio Damicelli

Oct. 24, 2022

Funded PhD Scholarship in Developmental Neurorobotics at Sheffield Hallam University (UK)

by Di Nuovo, Alessandro

About the Project This scholarship will support the PhD candidate to carry out frontier research in Developmental Neurorobotics, a combination of Neuromorphic Computing and Cognitive Developmental Robotics. The PhD candidate will work with the Professor Alessandro Di Nuovo and his team, who have been awarded funding by the EPSRC for his research in the field. We are looking for an outstanding student to work with the team of a new EPSRC project. The research will pioneer the new developmental neuromorphic paradigm, which will be a synergic combination that will go beyond the limitations of the individual paradigms: neuromorphic computing will provide efficient brain-like resources able to process a more accurate representation of the real world, meanwhile developmental robotics will deliver the missing learning mechanisms for complex applications of neuromorphic spiking neural networks. The short-term objective is to demonstrate feasibility and lay the foundation of a biologically plausible framework to simulate the human-like learning process of numerical and abstract cognition, a fundamental characteristic of human intelligence. The team long-term goal is to create an artificial mind for robots that 'grows up' like a child's brain. This will be underpinned by neuromorphic computing which emulates the deep-lying architecture of the brain and will allow it to interpret and adapt to situations. As well as enabling the creation of robots with a human-like ability to reason, behave and interact the creation of an artificial mind will boost research in life sciences disciplines such as neuroscience by allowing researchers to run biologically realistic simulations to test theories. By simulating information on the inner workings of the brain that could not otherwise be detected, it could enhance our understanding of neurodevelopmental and learning disorders and lead to new treatments. Eligibility Information on entry requirements can be found here<https://www.findaphd.com/common/clickCount.aspx?theid=147190&type=184&DID=6…> The ideal candidate should have a Masters degree in Neuromorphic Computing, Computational Neuroscience, Machine Learning, or closely related disciplines in AI and Robotics, excellent programming skills and experience in interdisciplinary research. How to apply Your application should be emailed to industry-innovation-admissions(a)shu.ac.uk<javascript:void(0)> by the closing date of 31 October 2022. Any interested candidates must contact the lead academic, Prof. Alessandro Di Nuovo, a.dinuovo(a)shu.ac.uk<javascript:void(0)>, to discuss your application. The application should explain how the candidate knowledge, skills and experience are relevant to the project short and long-term objectives. Start date for studentship: 01/02/2023 Interviews are scheduled for: 11/11/2022 For information on how to apply please visit https://www.shu.ac.uk/research/degrees<https://www.findaphd.com/common/clickCount.aspx?theid=147190&type=184&DID=6…> ________________________________ Funding Notes The PhD studentship provides tuition fees at UK level and a maintenance bursary at the UK Research Councils' national minimum doctoral stipend rate (£17,668 for 2022/23). The scholarship is available for three years of full-time. ________________________________ References Di Nuovo, A., McClelland (2019). Developing the knowledge of number digits in a child-like robot. Nature Machine Intelligence, 1(12), 594-605. Di Nuovo, A., & Jay, T. (2019). Development of numerical cognition in children and artificial systems: a review of the current knowledge and proposals for multi-disciplinary research. Cognitive Computation and Systems, 1(1), 2-11. Di Nuovo, A., & Cangelosi, A. (2021). Abstract Concept Learning in Cognitive Robots. Current Robotics Reports, 2(1), 1-8. Roy, Jaiswal, Panda, (2019). Towards spike-based machine intelligence with neuromorphic computing. Nature, 575(7784), 607-617. Krichmar (2018). Neurorobotics-A Thriving Community and a Promising Pathway Toward Intelligent Cognitive Robots. Frontiers in Neurorobotics, Vol. 12, p. 42. Furber (2016). Large-scale neuromorphic computing systems. Journal of Neural Engineering, 13(5), 51001. Sengupta, et al. (2019). Going deeper in spiking neural networks: VGG and residual architectures. Frontiers in Neuroscience, 13, 95. Quax, D'Asaro,van Gerven, (2020). Adaptive time scales in recurrent neural networks. Scientific Reports, 10(1), 11360. Alessandro Di Nuovo, PhD Professor of Machine Intelligence College of Business, Technology and Engineering Sheffield Hallam University, United Kingdom Email: a.dinuovo(a)shu.ac.uk<mailto:a.dinuovo@shu.ac.uk>

Oct. 23, 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 Director, Center for Neural Circuit Dynamics <https://www.stonybrook.edu/cncd/> Stony Brook University

Oct. 22, 2022

Brain Criticality 2022 Hybrid Meeting - Deadline October 23rd for virtual registration

by BATTAGLIA Demian

*** LAST DAYS TO REGISTER FOR VIRTUAL PARTICIPATION AND SUBMIT VIRTUAL POSTER ABSTRACT*** We are happy to announce that the next conference on “Criticality in Neural Systems 2022: Collective Behavior, Synchronization, and Complexity” will take place at the Porter Neuroscience Research Center (National Institute of Health, Bethesda, MD, USA) from Nov. 7 – 9th, 2022 (shortly before the SFN Meeting, San Diego) The conference will be held in a hybrid format, both in presence at NIH Bethesda and via Zoom. Presentations by the invited speakers, with ample time for discussions, including with online participants, will be complemented by a poster session (in presence and online) and by a selection of contributed spotlight presentations. Keeping line with previous editions of the Brain Criticality conferences series, this conference will present the latest experimental and theoretical advancements in the study of critical phenomena in brain activity and their functional relevance. While preserving emphasis on criticality, this edition will feature as well communications about general collective behavior and dynamic complexity in the brain (and other biological systems). REGISTRATION IS OPEN AND FREE ON https://braincriticality.org/ Deadline for virtual registration: October 23rd Deadline for abstract submission (with spotlight oral preference): October 9th Deadline for abstract submission (poster only): October 23rd Confirmed Speakers Ad Aertsen (Freiburg, Germany) Dante Chialvo (Buenos Aires, Argentina) Karin Dahmen (Urbana-Champaign, IL) Irene Giardina (Rome, Italy) Michelle Girvan (College Park, MD) Moritz Helias (Jülich, Germany) Henrik Jensen (London, UK) Arvind Kumar (Stockholm, Sweden) Anna Levina (Tübingen, Germany) Klaus Linkenkaer-Hansen (Amsterdam, the Netherlands) Simona Olmi (Sesto Fiorentino, Italy) Orit Peleg (Boulder, CO) Pawel Romanczuk (Berlin, Germany) Woodrow Shew (Fayetteville, AR) James Shine (Sidney, Australia) Samir Suweis (Padova, Italy) Enzo Tagliazucchi (Buenos Aires, Argentina) Bradley Voytek (La Jolla, CA) Ralf Wessel (St Louis, MO) Changsong Zhou (Hong Kong, Popular Republic of China) Organizers Dietmar Plenz (Bethesda, MD) Lucilla de Arcangelis (Caserta, Italy) Miguel Angel Munoz (Granada, Spain) Mauro Copelli (Recife, Brazil) Demian Battaglia (Marseille & Strasbourg, France) For more information visit our website https://braincriticality.org/ or contact us over email.

Oct. 21, 2022

Computational Neuroscience and Computational Neurology

by André Fabio Kohn

Computational Neuroscience has shown a tremendous development in the last decades, and we think it is ripe to contribute substantially to computational neurology. In selected cases, large-scale and multi-scale models encompassing sensory receptors, neurons, muscles, bones, joints and other structures can be modeled to represent different degrees of dysfunction of a specific subsystem associated with a given neurological pathology. The model simulations can shed light to early signs of the disease (earlier detection than with current diagnosis techniques) and provide estimates of the progression of disease as a function of different treatment courses. We show in a recent paper published in the Journal of Neural Engineering [ https://iopscience.iop.org/article/10.1088/1741-2552/ac91f8/pdf] how neuropathies associated with Guillain-Barré Syndrome can affect functional aspects of the control of foot movement in a controlled setting, which is suitable for clinical evaluation. Muscle electrical activity also was shown to be a useful quantifier of the demyelination process. The multi-scale model encompasses neuronal ionic channels of spinal cord neurons up to a model of the foot and its muscles acting around the ankle joint when controlling force and foot position in a controlled lab experiment. The extension of such an approach to other peripheral nervous disorders or to spinal cord related pathologies (e.g., motoneuron diseases) seems quite feasible, provided that parameter data from patients are available to realize a biologically compatible model. Andre Fabio Kohn, Ph.D., Professor of Biomedical Engineering, University of Sao Paulo

Oct. 20, 2022

Postdoc positions in nanoscale modeling of neurons, synapses or astrocytes

by Erik De Schutter

The Computational Neuroscience unit at the Okinawa Institute of Science and Technology (https://www.oist.jp <https://www.oist.jp/>), Japan has been spearheading nanoscale stochastic modeling of astrocytes, neurons and synapses (https://groups.oist.jp/cnu <https://groups.oist.jp/cnu>). We have two postdoctoral positions open and Japan is issuing visa for such positions. The selected candidates will build on previous work in modeling of cerebellar or hippocampal neurons, synapses or astrocytes, neurons and synapses using our STEPS software (http://steps.sourceforge.net <http://steps.sourceforge.net/>), research project depending on experience and interests of the candidate. Previous experience in neural modeling required, preferentially as subject of PhD. Competences: A recent PhD in a relevant discipline such as neuroscience, molecular biology, biophysics or biochemistry. Experience in programming in Python. Fluent English conversation and writing skills. Benefits / Offer: A competitive salary and relocation package are offered with an initial 2 year contract. This an ideal position to gain experience in a prominent computational neuroscience lab and take part in our international collaborations. Please contact Prof. Erik De Schutter (erik(a)oist.jp <mailto:erik@oist.jp>) for inquiries.

Oct. 20, 2022

SNUFA22 spiking neural network workshop program (Nov 9-10)

by Goodman, Daniel F M

We are delighted to announce the finalised program for the SNUFA22 spiking neural network workshop. It's free to attend but you do need to register in advance: http://snufa.net/2022/ 9-10 November 2022, European afternoons. (Subscribe to the Google Calendar<https://calendar.google.com/calendar/u/0?cid=OTYzMGJmOWIyZmJjZjNmNjE0ZDMzN2…>.) Invited speakers. * Charlotte Frenkel<https://chfrenkel.github.io/> (TU Delft) * Priya Panda<https://intelligentcomputinglab.yale.edu/> (Yale) * Yiota Poirazi<http://dendrites.gr/> (Institute of Molecular Biology and Biotechnology IMBB) * Yonghong Tian<https://www.pkuml.org/> (Peking University) Contributed talks: Thomas Limbacher, Ozan Özdenizci, Robert Legenstein (TU Graz) Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity M. Nardin, J. W. Phillips, W. F. Podlaski, S. W. Keemink (IST Austria) Nonlinear computations in spiking neural networks through multiplicative synapses A. Subramoney, K. K. Nazeer, M. Schöne, C. Mayr, D. Kappel (University of Bochum) Beyond Biologically Plausible Spiking Networks for Neuromorphic Computing A. Galloni, A. Peddada, A. Milstein (Rutgers) Behavioral Timescale Synaptic Plasticity (BTSP) for biologically plausible credit assignment across multiple layers via top-down gating of dendritic plasticity W. F. Podlaski, C. K. Machens (Champalimaud) Universal function approximation in balanced spiking networks through convex-concave boundary composition B. Yin, F. Corradi, and S. M. Bohte (CWI) Training Dynamic Spiking Neural Network via Forward Propagation Through Time Z. Liao, D. Hadjiabadi, S. Terada, I. Soltesz, A. Losonczy (Columbia) A biologically plausible inhibitory plasticity rule for world-model learning in SNNs C. B. Currin, K. Stecher, C. Pfeffer, G. Novarino, and T. P. Vogels (IST Austria) Bridging the gap between artificial models and cortical circuits Plus around 30 posters. Many thanks! Dan Goodman, Friedemann Zenke, Katie Schuman, Tim Masquelier

Oct. 19, 2022

PhD openings in computational neuroscience, cognitive science, machine learning

by Rava A. da Silveira

*PhD openings in computational neuroscience, cognitive science, and interfaces with machine learning* The lab of Rava Azeredo da Silveira invites applications for *Doctoral Student* positions at IOB, University of Basel. Research questions will be chosen from a range of topics in theoretical/computational neuroscience and cognitive science, involving either data analysis or theory, and drawing on recent machine learning approaches. Candidates with backgrounds in mathematics, statistics, artificial intelligence, physics, computer science, engineering, biology, and psychology are welcome. Experience with data analysis and proficiency with numerical methods, in addition to familiarity with neuroscience topics and mathematical and statistical methods, are desirable. Equally desirable are a spirit of intellectual adventure, eagerness, and drive. The positions will come with highly competitive work conditions and salaries. For details, see https://www.silveira-lab.com/openings. *Application deadline:* For full consideration, please apply by 15 November 2020. *How to apply:* Please send the following information *in one single PDF, to * *silveira(a)iob.ch* <silveira(a)iob.ch>*:* 1. letter of motivation; 2. statement of research interests, limited to two pages; 3. curriculum vitæ. In all email correspondence, please include the mention “APPLICATION-PHD” in the subject header, otherwise the application will *not* be considered. Please also arrange for three letters of recommendations to be sent to the same email address.

Oct. 18, 2022

Postdoc openings in computational neuroscience, cognitive science, machine learning

by Rava A. da Silveira

*Postdoctoral openings in computational neuroscience, cognitive science, and interfaces with machine learning* The lab of Rava Azeredo da Silveira invites applications for *Postdoctoral Researcher* positions at IOB, University of Basel. Research questions will be chosen from a range of topics in theoretical/computational neuroscience and cognitive science, involving either data analysis or theory, and drawing on recent machine learning approaches. Candidates with backgrounds in mathematics, statistics, artificial intelligence, physics, computer science, engineering, biology, and psychology are welcome. Experience with data analysis and proficiency with numerical methods, in addition to familiarity with neuroscience topics and mathematical and statistical methods, are desirable. Equally desirable are a spirit of intellectual adventure, eagerness, and drive. The positions will come with highly competitive work conditions and salaries. For details, see https://www.silveira-lab.com/openings. *Application deadline:* For full consideration, please apply by 15 November 2020. *How to apply:* Please send the following information *in one single PDF, to * *silveira(a)iob.ch* <silveira(a)iob.ch>*:* 1. letter of motivation; 2. statement of research interests, limited to two pages; 3. curriculum vitæ including a list of publications; 4. any relevant publications that you wish to showcase. In all email correspondence, please include the mention “APPLICATION-POSTDOC” in the subject header, otherwise the application will *not* be considered. Please also arrange for three letters of recommendations to be sent to the same email address.

Oct. 18, 2022

Fully-funded computational neuroscience PhD at the University of Manchester

by Caroline Lea-Carnall

Link to project: https://www.findaphd.com/phds/project/bbsrc-dtp-neural-network-models-to-in… About the Project Neuroplasticity is the mechanism that underpins the brain’s ability to learn. It is an umbrella term that encompasses multiple processes occurring at different spatial and temporal scales (1, 2). The most commonly discussed type of plasticity is long-term potentiation (LTP) which is defined as an increase in efficacy between synapses of two neurons. Experiments designed to measure LTP are often done in cell slices or cultures using patch-clamp techniques. However, we often want to promote (and measure) plasticity in humans but its not clear how changes in synaptic efficacy manifest in macroscopic imaging measurements such as magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), or electroencephalography (EEG) that are available for use in humans. This project aims to link our detailed cellular-level knowledge of plasticity processes with systems-level observations in humans and is focussed on answering the following 2 questions: 1. How can we modulate plasticity non-invasively in the brain? 2. How can we measure plasticity in vivo? To answer these questions you will combine computational modelling of biophysically realistic large-scale neural networks that exhibit plasticity with cutting edge neuroimaging techniques to test the model predictions. The model will be adapted so that its output can be compared to the three major imaging techniques described above and you will determine how changes in connectivity between and within regions in the model predict changes in our imaging metrics. There will be a particular focus on developing an EEG marker of plasticity as this currently does not exist. Finally, you will test the model predictions in an imaging study combining stimulation, EEG, MRI and MRS in a proof-of-concept experiment in humans. This will provide us with a deeper understanding of how to modulate and measure plasticity that can be deployed in the future for medical applications of brain stimulation such as in Parkinson’s disease, depression and pain control. Eligibility Applicants must have obtained or be about to obtain a First or Upper Second class UK honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science, engineering or technology. Before you Apply Applicants must make direct contact with preferred supervisors before applying. It is your responsibility to make arrangements to meet with potential supervisors, prior to submitting a formal online application. How To Apply To be considered for this project you MUST submit a formal online application form - full details on eligibility how to apply can be found on the BBSRC DTP website https://www.bmh.manchester.ac.uk/study/research/bbsrc-dtp/<https://www.findaphd.com/common/clickCount.aspx?theid=147611&type=184&DID=1…> Your application form must be accompanied by a number of supporting documents by the advertised deadlines. Without all the required documents submitted at the time of application, your application will not be processed and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered. If you have any queries regarding making an application please contact our admissions team admissions.doctoralacademy(a)manchester.ac.uk<javascript:void(0)> Equality, Diversity and Inclusion Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-in…<https://www.findaphd.com/common/clickCount.aspx?theid=147611&type=184&DID=1…> ________________________________ Funding Notes Studentship funding is for 4 years. This scheme is open to both the UK and international applicants. We are only able to offer a limited number of studentships to applicants outside the UK. Therefore, full studentships will only be awarded to exceptional quality candidates, due to the competitive nature of this scheme.

Oct. 18, 2022

Imbizo Deadline approaching fast----> Apply NOW/

by Tim Vogels

Dear all, The DEADLINE for the next IMBIZO is approaching very quickly. Don’t let this opportunity slip by if you are hoping to join the most diverse neuroscience summer school at the most beautiful beach in the world! If you know anyone who would benefit from an extraordinary computational neuroscience summer school, please distribute this information as widely as you can: IBRO-SIMONS COMPUTATIONAL NEUROSCIENCE IMBIZO #Imbizo2023 12 April - 7 May 2022, Noordhoek Beach, Cape Town, South Africa http://imbizo.africa/ <http://imbizo.africa/> Application deadline: 20th October 2022 The #Imbizo2023 is a southern hemisphere summer school aiming to promote computational neuroscience in Africa. It will bring together international and local students under the tutelage of the world's leading experts in the field. Like its international sister courses, this four-week summer school aims to teach central ideas, methods, and practices of modern computational neuroscience through a combination of lectures and hands-on project work. Mornings will be devoted to lectures on topics across the breadth of computational neuroscience, including experimental underpinnings and machine learning analogues. The rest of the day will be spent working on research projects under the close supervision of expert tutors and faculty. Individual research projects will focus on the modelling of neurons, neural systems, behaviour, the analysis of state-of-the-art neural data, and the development of theories to explain experimental observations. New this year is a week focused on neuroscience-inspired machine learning! Who should apply? This course is aimed at Masters and early-PhD level students though Honours or advanced undergraduates may also apply. Postdoctoral students who can motivate why the course would benefit them are also encouraged to apply, Students should have sufficient quantitative skills, (e.g. a background in mathematics, physics, computer science, statistics, engineering or related field). Some knowledge of neural biology will be useful but not essential. Experimental neuroscience students are encouraged to apply, but should ensure that they have a reasonable level of quantitative proficiency (i.e. at least second-year level mathematics or statistics and have done at least one course in computer programming). Essential details * Fee (which covers tuition, lodging, and meals): 1200 EUR Thanks to our generous sponsors, significant financial assistance is available to reduce and waiver fees for students, particularly for African applicants. We also hope to provide some travel bursaries for international students. If you are in need of financial assistance to attend the Imbizo, please state so clearly in the relevant section of your application. The Imbizo is planned to be hosted in person, with everyone following our COVID policy <https://imbizo.africa/covid-policy/>. If it is unsafe to hold the summer school, we will follow up with further information at the appropriate time. * Application deadline: 20th October 2022 * Notification of results: Early December 2022 Information and application https://imbizo.africa/ <https://imbizo.africa/> Questions? isicn.imbizo(a)gmail.com What is an Imbizo? \ɪmˈbiːzɒ\ | Xhosa - Zulu A gathering of the people to share knowledge. Incl. FACULTY such as... Demba Ba - Harvard University Adrienne Fairhall - Washington University Aza Allsop - Yale University David Sussillo - Google Leyla Isik - Johns Hopkins University Peter Latham - University College London Timothy Lillicrap - DeepMind Joseph Raimondo - University of Cape Town Mackenzie Mathis - EPFL Lausanne Evan Schaffer - Columbia University Henning Sprekeler - Technical University of Berlin Thomas Tagoe - University of Ghana Tim Vogels - Institute of Science and Technology Austria Blake Richards - McGill University Xaq Pitkow - Baylor College of Medicine Bianca Jones Marlin - Columbia University TUTORS Mohamed Abdelhack - Krembil Centre for Neuroinformatics Annik Carson - AI Redefined Spiros Chavlis - IMBB-FORTH Christopher Currin - Institute of Science and Technology Austria Nina Kudryashova- University of Edinburgh Marjorie Xie - Columbia University ORGANISERS Demba Ba (Harvard University) Christopher Currin (Institute of Science and Technology Austria) Peter Latham (Gatsby Unit for Computational Neuroscience) Joseph Raimondo (University of Cape Town) Emma Vaughan (Imbizo Logistics) Tim Vogels (Institute of Science and Technology Austria) Sponsors The Imbizo is made possible by the generous support from the Simons Foundation <https://www.simonsfoundation.org/> and the International Brain Research Organisation (IBRO) <https://ibro.org/> Organizational Affiliates University of Cape Town, University College London, Institute of Science and Technology Austria, TReND in Africa <http://trendinafrica.org/>, Neuroscience Institute <http://www.neuroscience.uct.ac.za/>, Gatsby Foundation <http://www.gatsby.org.uk/>, IBRO African Center for Advanced Training in Neurosciences at UCT

Oct. 18, 2022

Survey of user experiences in neuronal network modeling

by Anton Arkhipov

Dear Colleagues, Our NIH BRAIN Initiative-sponsored project (1U24NS124001) – a collaboration between teams at the Allen Institute and University of Illinois – focuses on disseminating tools for neuronal network modeling and supporting users. Would you be so kind to help us understand the needs and experiences of users in this field? We will very much appreciate it if you can fill out this brief survey: https://forms.gle/jFw6hFhY9dyDd25w5 It will take only 5 minutes, and the results will help guide future development of software and documentation for the community. Whether you use our tools or not, an expert or novice in modeling, we’d love to hear from you! Thank you so much. If you have any questions, please feel free to reach out by email. Best regards, Anton. Anton Arkhipov Associate Investigator T: 206.548.8414 E: antona(a)alleninstitute.org<mailto:antona@alleninstitute.org> [Text Description automatically generated] alleninstitute.org<https://alleninstitute.org> brain-map.org

Oct. 18, 2022

Application for ION Fellow independent position at University of Oregon

by Luca Mazzucato

We are announcing an open search for our new members of the inaugural *Institute of Neuroscience Fellows Program*, co-sponsored by the University of Oregon and the Knight Campus for Accelerating Scientific Impact. This program is aimed at recruiting *exceptional postdoctoral scholars whose interests lie at the interface between Systems and Computational Neuroscience*. The ION Fellow will have intellectual freedom to develop their *independent research* on the neural mechanisms of brain function across the entire range from experiments to theory, leveraging resources and mentorship from multiple labs participating in the Program. Research funds to support the independent project will be available to the Scholar to spend at their discretion. ION Fellows will play a central role in our intellectual community and will be encouraged to pursue collaborative projects that span the interests of multiple labs and faculty mentors. Our Institute has a strong culture of theory/experiment collaboration, which has been powered by the interdisciplinary approach of our trainees. The faculty will provide extensive training in both scientific aspects and career development with the goal of charting a successful path to independence for the ION Fellow. Our Institute features a wide range of expertise including sensory processing (visual, auditory and olfactory), motor control, naturalistic behavior, neuronal development, neural engineering, and brain-computer interfaces. Our newly established NeuroAI Center combines data science and computational approaches for modeling large neural and behavioral datasets and developing the new generation of brain-inspired Artificial Intelligence. While our main experimental labs participating in the program use mice as a model system, the ION Fellow will also have opportunities to work with laboratories working with humans, Zebra fish, fruit fly, and c. e*legans**.* We expect ION Fellows to establish a mentoring team including multiple faculty mentors. The Fellow will be a member of the NSF-funded Accelnet consortium "International network for brain-inspired computation," fostering collaborations between a large-network of computational neuroscience/AI labs. *Mini**mum qualifications* for this position include a PhD in Neuroscience, Physics, Biology, Mathematics, Computer Science, Engineering, Psychology, Human Neurophysiology, Statistics or a related discipline; and a track record of productive research, including publications. A competitive salary and benefits arrangement will be provided including travel funds. To apply please send your CV, a 1-2 page summary of research accomplishments, and a 1-2 page statement of research interests, to “lmazzuca at uoregon dot edu” with subject line “ION Fellow application”; please arrange to have 3 letters of reference sent to the same email address. Our Institute strongly advocates for inclusivity in science and we encourage applications from underrepresented groups. Application reviews will start on Nov. 1st and will continue until the position is filled. Participating labs include: Tim Gardner, Santiago Jaramillo, Michelle Marneweck, Luca Mazzucato, David McCormick, James Murray, Cris Niell, Matt Smear, Emily Sylwestrak

Oct. 18, 2022

Post-doctoral position in Systems Neuroscience at Yale

by Anirvan Nandy

[Apologies for cross-posting] The Nandy lab <https://nandylab.org/> and the Jadi lab <https://www.jadilab.org/> in the Departments of Neuroscience & Psychiatry at the Yale School of Medicine has an opening for a Postdoctoral Associate, to investigate the neural mechanisms of perception and attention. Applicants with the following skills are particularly encouraged to apply: (a) research background in systems or computational neuroscience, (b) expertise in electrophysiology in behaving animals, and/or (c) highly quantitative data analytic skills (possibly including computational modelling). The candidate will carry out high-density multi-areal electrophysiological recordings while animals are engaged in attention-demanding visual tasks. The individual will be required to train animals, generate electrophysiological data, and perform advanced statistical data analyses and modelling in a highly collaborative research environment. The position is initially for a period of 1 year, with scope for multi-year renewal subject to satisfactory progress. Candidates will be reviewed on a rolling basis until the position is filled. Yale provides an outstanding environment for conducting successful and rigorous postdoctoral training toward obtaining an independent research position. The neuroscience community at Yale is highly active and involves interdisciplinary collaborations across multiple academic units including the Departments of Neuroscience, Psychology, Psychiatry, Computer Science, Statistics & Data Science, Molecular, Cellular & Developmental Biology and more. The Wu Tsai Institute, Kavli Institute for Neuroscience, and the Swartz Center for Theoretical Neurobiology provide excellent opportunities for training and cross-disciplinary dialog. Yale and our labs are highly committed to promoting diversity among its students, faculty, and staff. Women, person with disabilities, protected veterans, individuals from underrepresented minority groups are strongly encouraged to apply. Interested candidates should e-mail their applications to anirvan.nandy(a)yale.edu <mailto:anirvan.nandy@yale.edu>. The application should include: (1) CV; (2) a one-page description of research interests; (3) contact information for 3 referees. -------------------------------------------------------------------------- Anirvan Nandy, PhD Yale Orthwein Scholar for Vision Science Dept. of Neuroscience | Kavli Institute | Wu Tsai Institute Yale University https://nandylab.org <https://nandylab.org/>

Oct. 17, 2022

Paid Research Internships in AI and Brain Research (CaCTuS)

by Helena Dalmau Felderhoff

-- Apologies for cross-posting -- Our international internship program, CaCTüS, offers paid research internships at the Max Planck Institute for Biological Cybernetics, the Max Planck Institute for Intelligent Systems and the AI Center in Tübingen & Stuttgart (Germany) to students who face significant constraints in their pursuit of a career in AI or brain research. We would be very grateful if you could help us reach students who may benefit from our program. You can do that by distributing the call for applications in your professional networks, among your colleagues and any interested students, or by sharing our posts on social media. You may find details on the program and links to our social media posts below. We thank you in advance for any support you are willing to give us. If you have any questions, please feel free to contact us. Kind regards, Helena Dalmau Felderhoff - on behalf of the CaCTüS Internship coordination team - About the CaCTüS Internship program <https://cactus-internship.tuebingen.mpg.de> cactus-internship.tuebingen.mpg.de The sciences of biological and artificial intelligence are rapidly growing research fields that need enthusiastic minds with a keen interest in solving challenging questions. The Max Planck Institutes for Biological Cybernetics and Intelligent Systems as well as the AI Center in Tübingen & Stuttgart (Germany) offer up to 10 students at the Bachelor or Master level paid three-months internships during the summer of 2023. Successful applicants will work with top-level scientists on research projects spanning machine learning, electrical engineering, theoretical neuroscience, behavioral experiments and data analysis. The CaCTüS Internship is aimed at young scientists who are held back by personal, financial, regional or societal constraints to help them develop their research careers and gain access to first-class education. The program is designed to foster inclusion, diversity, equity and access to excellent scientific facilities. We specifically encourage applications from students living in low- and middle-income countries which are currently underrepresented in the Max Planck Society research community. Application deadline: 4 December 2022 Social Media Links Twitter: <https://twitter.com/MPICybernetics/status/1581941564699336704> https://twitter.com/MPICybernetics/status/1581941564699336704 Facebook: <https://www.facebook.com/MPICybernetics/photos/a.1701083666787308/343340166 3555491> https://www.facebook.com/MPICybernetics/photos/a.1701083666787308/3433401663 555491 Instagram: <https://www.instagram.com/p/Cjz1mpssJjm/> https://www.instagram.com/p/Cjz1mpssJjm/ LinkedIn: <https://www.linkedin.com/feed/update/urn:li:activity:6987707261393502208> https://www.linkedin.com/feed/update/urn:li:activity:6987707261393502208 ************************************************ CaCTüS Internship Coordination Office Max Planck Institute for Biological Cybernetics Max-Plank-Ring 8 72076 Tübingen Germany <mailto:cactus-internship@tuebingen.mpg.de> cactus-internship(a)tuebingen.mpg.de <http://cactus-internship.tuebingen.mpg.de/> http://cactus-internship.tuebingen.mpg.de/ ************************************************

Oct. 17, 2022