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Sixth Groningen Spring School on Cognitive Modeling
by Thomas Dec. 16, 2022

Dec. 16, 2022

____________________ Sixth Groningen Spring School on Cognitive Modeling – ACT-R, Nengo, PRIMs – Date: 27-31 March 2023 Location: Groningen, the Netherlands Fee: € 305 (late fee after February 26 will be € 355) More information and registration: www.cognitive-modeling.com/springschool ____________________ Dear colleagues and students, We are excited to announce the sixth Spring School on Cognitive Modeling in Groningen, from 27-31 March 2023! This time, the Spring School will cover three different modeling paradigms: ACT-R, Nengo, and PRIMs. Each of these topics consists of a series of lectures, as well as a number of hands-on exercises (tutorials). Past years have shown that students get most out of the spring school if they really emerge themselves into one modeling paradigm. We therefore recommend you choose one topic for which you will attend both the lectures as well as the tutorials. In addition, you can select a second paradigm, for which you attend the lectures only. To give students a broader picture, there will also be three guest lectures throughout the week. These lectures each give an introduction to yet another modeling paradigm: accumulator models (Leendert van Maanen), error-driven learning models (Jacolien van Rij), and dynamical systems (Herbert Jäger). Everyone is encouraged to attend those lectures. To round of the program, there will be a poster session, where students present themselves and their research, as well as a city tour, and our (in)famous spring school dinner. Registration is now open. Please feel free to forward the information to anyone who might be interested in the Spring School. We are looking forward to welcoming you (again) in Groningen, The Spring School team springschool(a)rug.nl ______________ ACT-R Teachers: Jelmer Borst, Stephen Jones, & Katja Mehlhorn (University of Groningen) Website: http://act-r.psy.cmu.edu ACT-R is a high-level cognitive theory and simulation system for developing cognitive models for tasks that vary from simple reaction time experiments to driving a car, learning algebra, and air traffic control. ACT-R can be used to develop process models of a task at a symbolic level. Participants will follow a compressed five-day version of the traditional summer school curriculum. We will also cover the connection between ACT-R and fMRI. Nengo Teacher: Terry Stewart and Andreas Stöckel (University of Waterloo) Website: http://www.nengo.ca Nengo is a toolkit for converting high-level cognitive theories into low-level spiking neuron implementations. In this way, aspects of model performance such as response accuracy and reaction times emerge as a consequence of neural parameters such as the neurotransmitter time constants. It has been used to model adaptive motor control, visual attention, serial list memory, reinforcement learning, Tower of Hanoi, and fluid intelligence. Participants will learn to construct these kinds of models, starting with generic tasks like representing values and positions, and ending with full production-like systems. There will also be special emphasis on extracting various forms of data out of a model, such that it can be compared to experimental data. PRIMs Teacher: Niels Taatgen (University of Groningen) Website: https://www.ai.rug.nl/~niels/prims/index.html How do people handle and prioritize multiple tasks? How can we learn something in the context of one task, and partially benefit from it in another task? The goal of PRIMs is to cross the artificial boundary that most cognitive architectures have imposed on themselves by studying single tasks. It has mechanisms to model transfer of cognitive skills, and the competition between multiple goals. In the tutorial we will look at how PRIMs can model phenomena of cognitive transfer and cognitive training, and how multiple goals compete for priority in models of distraction. ______________ — Thomas Tiotto, PhD Candidate, CogniGron - Groningen Cognitive Systems and Materials University of Groningen Nijenborgh 9, 9747 AG Groningen, The Netherlands Email: t.f.tiotto(a)rug.nl Profile: https://www.rug.nl/staff/t.f.tiotto/ Office: 5161 0318 Sent with Spark

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Call for Papers - IEEE T-MBMC - Special Issue on Bio-Chem-ICTs
by Murat Kuşcu Dec. 15, 2022

Dec. 15, 2022

IEEE Transactions on Molecular, Biological and Multi-Scale Communications Special Issue on Bio-Chem-ICTs: Synergies between Bio/Nanotechnologies and Molecular Communications https://www.comsoc.org/publications/journals/ieee-tmbmc/cfp/bio-chem-icts-s… ----------------------- CALL FOR PAPERS Molecular Communications (MC) is a fundamental means of information exchange ubiquitously observed in nature. It has recently attracted the attention of researchers who have been working in information and communication technologies (ICT) and striving to create cooperative ‘nanonetworks’ of artificial nanomachines, which can be interfaced with or immersed in natural biological systems. Application of ICT tools to this natural modality of communications has laid the foundations of bio-inspired, engineered MC systems, and also contributed to the understanding of natural MC networks. It is no wonder that such fundamental form of communications has been a topic of significant interest in many diverse research fields beyond ICT, such as synthetic biology, systems chemistry, micro/nanorobotics, network medicine, biophysics and physiology, biochemical sensing, lab- and organ-on-chips, bio-interfaces, molecular and biological computing, drug discovery, design and delivery. However, different languages are typically adopted by different fields to refer to the same phenomenon that the ICT researchers call molecular communications, such as chemical communications, biological/cell signaling, interaction networks, which all fundamentally denote information transfer via mass transport and/or biochemical reactions and interactions. Despite the significant overlap in the problem and the application domain, not only the language but also the research methodologies and the solution approaches are diverse, partly due to the apparent lack of strong links between different research communities. On the other hand, closer interactions between these disciplines can create important synergies that can help collaboratively target more challenging research problems and develop unprecedented applications, where the power of true interdisciplinarity is unleashed. These interactions can also help better identify the common motifs in the heterogeneous sea of molecular communication problems and scenarios comprising both biotic and abiotic systems, and help reframe and standardize the way we approach biological and bio-inspired communications in the hope of enabling a common scientific and engineering language. The aim of this Special Issue is to facilitate such interactions by bringing together the contributions of prominent researchers from diverse fields that share a common denominator with the ICT approach to MC. Reflecting different perspectives on natural and engineered molecular communications, and appreciating the diversity of approaches and methodologies, the Special Issue will ultimately help identify the potential interaction pathways between different research areas and communities, that can lead to fruitful collaborations and synergy. To this end, we solicit original contributions (technical or position/survey/tutorial/perspective articles) on a very diverse set of topics including but not limited to: ** Molecular communication among synthetic cells, and between synthetic and natural cells ** Molecular communication among nanoparticles, and between nanoparticles and natural/synthetic cells ** Collective micro/nanorobotic swarms and active matter based on molecular communications ** Physical limits to communication, sensing, and information processing in natural and synthetic bio/nano systems ** Network medicine, communication and network biomarkers of diseases ** Engineering of protein-protein and other molecular interactions, de novo design of proteins and artificial receptors for sensing and molecular communications ** Semantic information in biological networks ** Bio-interfaces (e.g., neural interfaces) relying on molecular interactions, redox reactions, and ionic carriers ** New sensing techniques and chemical & biosensor architectures targeting dynamic bio/chemical signals ** New nanomaterials and device architectures for bio-nano interfaces, and micro/nanomachines & molecular machines capable of molecular communications ** Drug design techniques exploiting molecular interactions, network-based approaches to drug discovery ** Smart drug delivery systems and techniques ** Biological and molecular computing ** Signaling aspects of lab-on-a-chip, organ-on-a-chip, multi-organ-on-a-chip, body-on-a-chip, disease-on-a-chip applications --------------------------- IMPORTANT DATES Manuscript Submission Deadline: 15 March 2023 First Notification: 30 April 2023 Acceptance Notification: 30 May 2023 Final Manuscript Due: 30 June 2023 Publication Date: September 2023 --------------------------- GUEST EDITORS Murat Kuscu Department of Electrical and Electronics Engineering Koc University, Turkey Email: mkuscu(a)ku.edu.tr Pasquale Stano Department of Biological and Environmental Sciences and Technologies University of Salento, Italy Email: pasquale.stano(a)unisalento.it Gregory F. Payne Institute for Bioscience and Biotechnology Research University of Maryland, USA Email: gpayne(a)umd.edu Bige D. Unluturk School of Computer Science and Electronic Engineering Michigan State University, USA Email: unluturk(a)msu.edu Malcolm Egan University of Lyon, Inria, INSA-Lyon, CITI, France Email: malcolm.egan(a)inria.fr Michael T. Barros School of Computer Science and Electronic Engineering University of Essex, UK Email: m.barros(a)essex.ac.uk --------------------------- SUBMISSION GUIDELINES Prospective authors should submit their manuscripts following the IEEE TMBMC guidelines ( https://www.comsoc.org/publications/journals/ieee-tmbmc/information-for-aut… ). Authors should submit a manuscript through Manuscript Central ( https://mc.manuscriptcentral.com/tmbmc) ---------------------------

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Interdisciplinary PhD program in London, UK
by Silver, Angus Dec. 15, 2022

Dec. 15, 2022

Interdisciplinary PhD program in London, UK – call for 2023 applications – deadline 10th January. The London Interdisciplinary Biosciences Consortium (LIDo) Doctoral Training Partnership (DTP) is a BBSRC funded collaborative partnership offering world-class interdisciplinary research. LIDo unites an exciting team of outstanding universities and unique specialist institutions to provide innovative cutting-edge interdisciplinary research in the heart of one of the world's most vibrant and scientifically stimulating cities. LIDo will be offering 41 fully funded studentships in September 2023 across our DTP and iCASE routes of entry; these include home tuition fees and a tax-free stipend in the region of £19,668. A maximum of 11 of these positions can be offered to students eligible for overseas fee rates, where LIDo will cover the full fee amount. DTP Route In the first year of the programme DTP students will undertake two 4-month research projects in different partner institutions, selecting from a catalogue of over 200 topics. The choice of PhD topic is finalised after the second rotation project. Research opportunities are available across the breadth of BBSRC remit. Exemplar projects can be found on our website: https://www.lido-dtp.ac.uk/projects and DTP students will have the opportunity to contact potential supervisors in the Spring ahead of our call for projects. LIDo is particularly keen to welcome students from mathematics, computer science, engineering and the physical sciences who are eager to apply their skills and experience to biological problems and students from the plant sciences for exciting new projects available at our specialist academic and associate partners. All DTP students undertake a compulsory 3-month internship (PIPS) during their PhD to gain experience and context for careers where the transferable skills developed during their PhD programme can be usefully employed. iCASE Route Industrial collaborative (iCASE) students begin working on their named project from the start of the course. These projects represent genuine partnerships between academics within the LIDo consortium and industrial colleagues, allowing students to experience both distinctive environments in a mutually productive and supportive team and an extended placement of 3-18 months with their non-academic partner. Training and Cohort Building During the first-year, students will receive advanced training in fundamental and advanced mathematical, computational, and statistical skills for interdisciplinary and systems biology research. Expert in-house training in biological concepts and exposure to the history, trends and structure of the biotechnology and pharmaceutical industries make up the remaining first year teaching. Each year a week of cross research council remit teaching cushions the two rotations providing students the opportunity to hear from academic, industry, government, and not-for-profit speakers on a range of topics in the boundaries of BBSRC remit. The extraordinary LIDo teaching and research-intensive environment sits within a framework of robust and established cohort building activities, culminating each year in an academic retreat for the students. Application We enthusiastically invite applications by all highly motivated students from a wide range of academic backgrounds including biological, physical, computational, engineering or mathematical disciplines. Applicants must hold, or be expected to achieve, a first or high upper second-class honours degree (or equivalent), or an MSci or other Masters degree. For details on how to apply and the link to our online application form please go to: www.lido-dtp.ac.uk/apply<http://www.lido-dtp.ac.uk/apply> The application window will close on Tuesday 10th January 2023 at 5pm. R. Angus Silver, FRS Professor of Neuroscience and Wellcome Trust Principal Research Fellow Department of Neuroscience, Physiology and Pharmacology University College London Gower Street London WC1E 6BT Tel : 020 7679 7830 www.ucl.ac.uk/silverlab/

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Associate Research Scholar at Columbia University
by Michael Woodford Dec. 15, 2022

Dec. 15, 2022

*Position for Associate Research Scholar with the Cognitive and Behavioral Economics Initiative, Columbia University* The Cognitive and Behavioral Economics Initiative (CBEI) at Columbia University invites applications for an Associate Research Scholar (ARS) position to begin May 1, 2023 or later. The appointment will initially be for one year but is renewable based on satisfactory performance and availability of funding. The Associate Research Scholar will facilitate research on number cognition and the role of imprecise number representations as a source of errors and biases in economic decisions. A focus of the research will be the comparative evaluation of alternative quantitative models of the resource constraint that limits the precision of number representations, and the way in which these representations change depending on the statistics of the decision problems that are presented and, on the time allowed for mental processing. The Associate Research Scholar will conduct behavioral experiments, develop and test computational models of cognitive processes, and participate in data analysis and manuscript preparation, under the direction of Prof. Michael Woodford. *Qualifications* Applicants must have a Ph.D. in Economics, Neuroscience, Computer Science, Physics, or a related discipline, and at least three years of postdoctoral experience in related research. The ideal candidate will have strong computational skills, and experience conducting behavioral experiments, as well as superior motivation, drive, and demonstrated aptitude for research. Previous experience with interdisciplinary collaboration is strongly desired. For additional details and instructions for how to apply, see the job posting at https://academic.careers.columbia.edu/#!/108222.

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Spring School INTERDISCIPLINARY COLLEGE 2023: Invitation to Participate
by Herbert Jaeger Dec. 14, 2022

Dec. 14, 2022

The Interdisciplinary College (https://interdisciplinary-college.org/) is an annual one-week spring school, now in its 24th year. It offers a dense 4-track state-of-the-art course program in the wider sciences of intelligent/cognitive systems: Cognitive and Computational Neuroscience, Psychology, Machine Learning, AI and Philosophy. The perspective and mission is decidedly interdisciplinary. The 2023 event will take place in Guenne, Lake Moehne, Germany, on March 12-17, 2023 Chairs: Elisabeth Zimmermann, Gregor Schöner Each IK is centered on a *focus theme*. In 2023 the focus is on the role that physical interaction of an agent (with the environment, other agents, or its own body) plays for cognition. An offering of about 25 courses (each course 4-6 hours) is grouped under the perspectives of Movement & Bodily Experience; Neural Dynamics and Grounded Cognition; Experiencing Self and Others; Engaging with Technology & Things. The IK is also a unique social and networking event. Minds meet, music is played, and friends are made in long evening and night sessions in the welcoming conference site at Lake Moehne. While the IK has traditionally been mainly a European event, participants from outside Europe are highly welcome! Please visit https://interdisciplinary-college.org/ for the detailed program, venue and registration and everything else, including the IK's 40-year (pre-)history, and a totally seductive 6-min video on the startpage. --- 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 web: www.ai.rug.nl/minds/ -- 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 web: www.ai.rug.nl/minds/

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Computational Neuroscience PhD position - Newcastle, UK
by Andrej Bicanski Dec. 12, 2022

Dec. 12, 2022

Dear Colleagues, Please circulate this to any students that may be interested in a computational neuroscience PhD. The Topic: Modelling the staggered development and the decline with age of spatial coding in the mammalian brain + data analysis of single neuron recordings. In particular, the student will model the interactions between various spatial cells (head direction, place cells, etc) - e.g., in Matlab/Python. Candidates: This could be an interesting project for neuroscience/psychology graduates wanting to get into modelling. Students from outside these fields with a quantitative/programming background are welcome to apply too. Where: In sunny Newcastle, North UK, at Newcastle University, UK (with me), with a rotation in the lab of Prof. Colin Lever (Durham, UK, co-supervisor) Funding: Fully funded, for 4 years by the BBSRC. International and UK students can apply. Fees are covered! BBSRC Liverpool/Durham/Newcastle DTP3 scheme. Deadline: 9th of January Link: https://www.findaphd.com/phds/project/modelling-the-staggered-development-a…<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.finda…> For more info on the application process visit the BBSRC DTP website: https://www.nld-dtp.org.uk/how-apply<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nld-d…> Happy to receive informal inquiries prior to application. Best wishes, Andrej Dr Andrej Bicanski School of Psychology & Biosciences Institute Faculty of Medical Sciences Newcastle University www.andrejbicanski.com

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COSYNE 2023: Travel grants, Registration, Tutorials
by Tomas Hromadka Dec. 9, 2022

Dec. 9, 2022

==================================================== Computational and Systems Neuroscience 2023 (Cosyne) MAIN MEETING 09 - 12 March 2023 Montreal WORKSHOPS 13 - 14 March 2023 Mont-Tremblant www.cosyne.org ==================================================== IMPORTANT DATES Registration is now open. Travel grants applications are now open. Travel grant application deadlines *31 December 2022, 11.59PM PST (Undergraduate Travel Grant)* 24 January 2023, 11.59PM PST (Other travel grants) ---------------------------------------------------- COSYNE MEETING & WORKSHOPS ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The MAIN MEETING is single-track. A set of invited talks is selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. The WORKSHOPS feature in-depth discussion of current topics of interest, in a small group setting. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, neuromodulation, and computation with spiking networks. ----------------------------------------------- TRAVEL GRANTS ----------------------------------------------- Applications are now open for travel grants to attend the conference. Each awardee will receive at least $500 to help offset the costs of travel, registration, and accommodations. Larger grants may be available to those traveling from outside North America. Special consideration is given to scientists who have not previously attended the meeting, under-represented minorities, students who are attending the meeting together with a mentor, undergraduate students, and authors of submitted Cosyne abstracts. We currently offer five travel grant programs for New Attendees, Presenters, Mentors, Undergraduates, and Childcare travel grants. For details on applying, see www.cosyne.org/travel-grants. ---------------------------------------------------- COSYNE TUTORIALS ---------------------------------------------------- Cosyne 2023 will host tutorial sessions on 09 March 2023. For details on Cosyne tutorials please visit www.cosyne.org/tutorials. Cosyne 2023 Tutorial Session Sponsored by the Simons Foundation Topic: Methods in Reinforcement Learning for Neuroscience Speaker: Kimberly Stachenfeld (DeepMind) Kimberly Stachenfeld is a Research Scientist at DeepMind. Her research spans topics in Computational Neuroscience and Machine Learning, and focuses on the general question of how to learn structured, expressive world models that enable flexible reasoning. In ML, she is specifically interested in methods and applications for learned forward models using graph neural networks, and in Neuroscience, she mainly works on mathematical models of hippocampal representations to efficient, scalable RL learning. Learn to Use the International Brain Laboratory (IBL) Brainwide Map Dataset Tutorial The IBL recently released a Brainwide Map of neural activity during decision-making! It consists of 547 Neuropixel recordings of 32784 neurons across 194 regions of the mouse brain, and we want to make it easy for you to use it to test your own hypotheses. At this tutorial we’ll teach you how to use our API, ONE, to search and download datasets, and will show you how to do basic analysis such as raster plots, single cell PSTHs, and brain region averages. INVITED SPEAKERS Demba Ba (Harvard University) Camilla Bellone (University of Geneva) Frans de Waal (Emory University) Tatiana Engel (Cold Spring Harbor Laboratory) Robert Froemke (New York University) Catherine Hartley (New York University) Sheena Josselyn (SickKids) Adam Kepecs (Washington University) Tim Lillicrap (DeepMind) Mackenzie Mathis (École Polytechnique Fédérale de Lausanne) Srdjan Ostojic (École Normale Supérieure) Anne-Marie Oswald (University of Chicago) Nathalie Rochefort (University of Edinburgh) Maryam Shanechi (University of Southern California) Kimberly Stachenfeld (DeepMind) ORGANIZING COMMITTEE General Chairs: Laura Busse (LMU Munich) and Tim Vogels (IST Austria) Program Chairs: Jessica Cardin (Yale) and Blake Richards (McGill) Workshop Chairs: Anna Schapiro (U Penn) and Andrew Saxe (Oxford) Tutorial Chair: Kanaka Rajan (Mount Sinai) DEIA Committee: Hysell Oviedo (CUNY) and Aman Saleem (UCL) Undergraduate Travel Chairs: Angela Langdon (Princeton) and Sashank Pisupati (Princeton) Fundraising Chair: Michael Long (NYU) Social Media Chair: Grace Lindsay (Columbia) Audio-Video Media Chair: Carlos Stein Brito (EPFL) Poster Design: Xaq Pitkow (Rice) PROGRAM COMMITTEE Jessica Cardin (Yale) Co-chair Blake Richards (McGill) Co-chair Yashar Ahmadian (Cambridge) Mark Andermann (Harvard) Omri Barak (Technion) Brice Bathellier (Paris) Yoram Burak (Hebrew University) Johannes Burge (U Penn) Chandramouli Chandrasekaran (Boston U) SueYeon Chung (Columbia) Jeremiah Cohen (Allen Inst) Anne Collins (Berkeley) Christine Constantinople (NYU) Carina Curto (Penn State) Jan Drugowitsch (Harvard) Tatiana Engel (CSHL) Sean Escola (Columbia) Annegret Falkner (Princeton) Kevin Franks (Duke) Rainer Friedrich (FMI Basel) Andrea Hasenstaub (UCSF) Monika Jadi (Yale) Santiago Jaramillo (U Oregon) Kohitij Kar (MIT) Narayanan Kasthuri (U Chicago) Jens Kremkow (Berlin) Guillaume Lajoie (MILA) Sukbin Lim (Shanghai) Scott Linderman (Stanford) Ashok Litwin-Kumar (Columbia) Mackenzie Mathis (EPFL) Paul Miller (Brandeis) Ida Momennejad (Microsoft) Eilif Muller (U Montreal) Marieke Mur (Western U) Kathy Nagel (NYU) Daniel O'Connor (Johns Hopkins) Hysell Oviedo (CUNY) Il Memming Park (Stony Brook) Joseph Paton (Champalimaud) Adrien Peyrache (McGill) Xaq Pitkow (Rice) Kanaka Rajan (Mount Sinai) Nathalie Rochefort (Edinburgh) Aman Saleem (UCL) Cristina Savin (NYU) Tatyana Sharpee (Salk) Aparna Suvrathan (McGill) Saori Tanaka (ATR) Daniela Vallentin (MPI Ornithology) Melissa Warden (Cornell) Brad Wyble (U Penn) Marta Zlatic (Cambridge) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) Anne-Marie Oswald (U Chicago) CONTACT meeting [at] cosyne.org COSYNE MAILING LISTS Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See www.cosyne.org/mailing-lists for details.

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Postdoctoral Swartz Fellowships in Computational Neuroscience at Yale
by Murray, John Dec. 9, 2022

Dec. 9, 2022

Postdoctoral Swartz Fellowships in Theoretical and Computational Neuroscience at Yale University The Swartz Program for Theoretical Neuroscience at Yale University invites applications for up to two postdoctoral positions in Theoretical and Computational Neuroscience, with flexible start date in 2022. Competitive candidates include those with a strong quantitative background who wish to gain neuroscience research experience. We especially encourage candidates with an interest in collaborating directly with experimental neuroscientists. The candidates will be expected to perform theoretical/computational studies relevant to one or more laboratories affiliated with the Swartz Program at Yale (Jessica Cardin, Michael Crair, Damon Clark, Jonathan Demb, George Dragoi, Thierry Emonet, Michael Higley, Joe Howard, Monika Jadi, Jamie Jeanne, Alfred Kaye, Liang Liang, Benjamin Machta, John Murray, Anirvan Nandy, Ilker Yildririm, Steven Zucker). Applicants will be encouraged to participate in neuroscience and quantitative biology community at Yale, including through the Wu-Tsai Institute (https://wti.yale.edu/) and the Quantitative Biology Institute (https://qbio.yale.edu/) Candidates must hold a Ph.D. or equivalent degree by the time of beginning the fellowship. Please send a CV, selected (p)reprints, contact information for two or three references, and a statement of research interests including which laboratories at Yale are of interest. All application materials should be sent to the following e-mail address with "Swartz" in the email title: john.murray(a)yale.edu<mailto:john.murray@yale.edu>. Review of applications will begin January 7, 2023 and continue until positions is filled. For any questions, please contact John Murray. Yale University is an affirmative action/equal opportunity employer. Yale values diversity in its faculty, students, and staff and especially welcomes applications from women and underrepresented minorities. https://neurojobs.sfn.org/job/35847/postdoctoral-swartz-fellowship-position… John D. Murray ----------------------------------------------- Associate Professor of Psychiatry, Physics, and Neuroscience Wu Tsai Institute Yale University murraylab.org<https://murraylab.org/> -----------------------------------------------

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Post-Doctoral position in Cognitive and Sensorimotor Neuroscience on human gargalesis | Donders Institute
by Konstantina Kilteni Dec. 9, 2022

Dec. 9, 2022

Dear colleagues, We are excited to announce an opening postdoctoral position at our new lab at Donders Institute for Brain, Cognition and Behaviour, to work on a starting ERC project on gargalesis (tickle) perception: https://cordis.europa.eu/project/id/101039152. The main research focus of the project concerns when, where, how and why we interpret a touch applied on our body as ‘ticklish’. To address these questions, we will combine robotic technology, somatosensory psychophysics, neuroimaging (fMRI with focus on MVPA), brain stimulation (TMS), and advanced statistical modelling techniques. Requirements: • You should hold a PhD in the field of Neuroscience, Psychology, Cognitive Science, Biomedical Sciences, Engineering, or a related field. • You have skills and documented experience in collecting and analysing psychophysical, physiological, and behavioural data, as well as in analysing fMRI data, including the use of MVPA methods. • You have experience with, or are interested in, statistical and computational modelling. • You have a passion for research on the interface between neuroimaging, psychology and cognitive science. • You are curious, ambitious, and are able to work independently. • You are a team player with strong communication and coordination skills. • You have excellent English language skills and academic writing skills. Candidates will contribute to all steps of the research from literature review to implementation of study design, data collection, data analysis and preparation of manuscripts. The position is available for 1 year with the possibility for continuation for 2 more years, starting soon after the application deadline (with some flexibility on the starting date). For further information, please follow the link: https://www.ru.nl/en/working-at/job-opportunities/postdoctoral-researcher-i… Deadline of applications: January 15th, 2023 Interviews: January 25th, 2023 We are very curious and very excited about our research. Join us!! Konstantina Kilteni, Ph.D. Assistant Professor Department of Neuroscience | Karolinska Institutet Solnavägen 9 | 17165 Stockholm | Sweden https://www.kiltenilab.org/ |https://ki.se/en/neuro/kilteni-laboratory När du skickar e-post till Karolinska Institutet (KI) innebär detta att KI kommer att behandla dina personuppgifter. Här finns information om hur KI behandlar personuppgifter<https://ki.se/medarbetare/integritetsskyddspolicy>. Sending email to Karolinska Institutet (KI) will result in KI processing your personal data. You can read more about KI’s processing of personal data here<https://ki.se/en/staff/data-protection-policy>.

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PhD student position in Machine Learning: Theoretically motivated deep learning
by Tony Lindeberg Dec. 9, 2022

Dec. 9, 2022

PhD student position in Machine Learning: Theoretically motivated deep learning At the Division of Computational Science and Technology at KTH we are seeking a new PhD student in Machine Learning / Computer Vision to handle scale-dependent information in image data. In our research, we develop deep networks for processing image data that handle scaling transformations and other image transformations in a theoretically well-founded manner. Our research in this area comprises both theoretical modelling of the influence of image transformations on different architectures for deep networks as well as experimental evaluations of such networks on benchmark datasets to explore their properties. The work also comprises the creation of new benchmark datasets, to enable characterization of properties of deep networks that are not covered by existing datasets. For examples of our previous work in this area, see https://www.kth.se/profile/tony/page/deep-networks Within the scope of this PhD student position, you will work on and contribute to the research frontier regarding scale-covariant or scale-equivariant deep networks and/or deep networks parameterised in terms of Gaussian derivatives, on specific research topics that we choose together within the scope of the research project ”Covariant and invariant deep networks” that finances this position. The overall goal is to develop new architectures for deep networks that can generalise to scaling variations that are not spanned by the training data, and which can achieve higher robustness to variabilities in test data, as well as enable more efficient training with lower requirements concerning the amount of training data. The candidate should have very good knowledge in mathematics (analysis and linear systems, which we use for modelling convolution transformations and geometric image transformations) as well as in structured programming to write code that is easy to use for making experiments with, maintain and develop and share with colleagues. You must have very good knowledge about programming deep networks in Python, PyTorch is meritorious. Knowledge in computer vision and image analysis is strongly meritorious. For further information and information about how to apply, see https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:567595/wher… [cid:FD2B374F-C472-4895-ADA7-B3CD5419FD22@csc.kth.se] Tony Lindeberg Professor of Computer Science — Computational Vision KTH Royal Institute of Technology Computational Brain Science Lab Division of Computational Science and Technology, CST SE-100 44 Stockholm, Sweden Phone: +46 8 790 6205 https://www.kth.se/profile/tony/

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December 15 Deadline; Wu Tsai Postdoctoral Fellowship
by giovanna.guerrero-medina＠yale.edu Dec. 9, 2022

Dec. 9, 2022

The deadline to apply for a Wu Tsai Postdoctoral Fellowship is December 15, 2022. Please share the program details and the attached flyer with soon-to-be or recent PhDs outside of Yale who are enthusiastic about interdisciplinary research focused on cognition. The program provides a generous stipend for up to three years, funding for training and relocation, cohort-based professional development activities, and access to state-of-the-art facilities at Yale dedicated to integrative studies of the mind. International applicants are welcome. The Wu Tsai Postdoctoral Fellowship features opportunities for experimentalists and computationalists. The Computational Track is designed for scientists with expertise in computer science, data science, machine learning, artificial intelligence, applied math, or related fields who want to pursue independent research projects with Yale labs and use their skills to further our understanding of human cognition. The Experimental Track is for scientists wishing to work on co-mentored long-term projects in defined and compelling interdisciplinary neuroscience areas. Visit the Institute's website for a complete list of research projects. We encourage applications from scientists interested in contributing to diversity, equity, and inclusion in science. Find more information, past awardees, and application instructions here: https://wti.yale.edu/initiatives/postdoctoral. Best, Giovanna Guerrero-Medina, PhD She/Her/Ella Assistant Director for Diversity Equity & Inclusion, Wu Tsai Institute at Yale giovanna.guerrero-medina(a)yale.edu wti.yale.edu

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Announcing Okinawa/OIST Computational Neuroscience Course 2023
by Erik De Schutter Dec. 8, 2022

Dec. 8, 2022

OKINAWA/OIST COMPUTATIONAL NEUROSCIENCE COURSE 2023 Methods, Neurons, Networks and Behaviors June 19 to July 6, 2023 Okinawa Institute of Science and Technology Graduate University, Japan https://groups.oist.jp/ocnc <https://groups.oist.jp/ocnc> The aim of the Okinawa/OIST Computational Neuroscience Course is to provide opportunities for young researchers with theoretical backgrounds to learn the latest advances in neuroscience, and for those with experimental backgrounds to have hands-on experience in computational modeling. We invite graduate students and postgraduate researchers to participate in the course, held from June 19th through July 6th, 2023 at an oceanfront seminar house of the Okinawa Institute of Science and Technology Graduate University. Applications are through the course web page (https://groups.oist.jp/ocnc <https://groups.oist.jp/ocnc>) only; January 1 - January 31, 2023. Applicants will receive confirmation of acceptance end of March. Like in preceding years, the 18th OCNC will be a comprehensive three-week course covering single neurons, networks, and behaviors with ample time for student projects. The first week will focus exclusively on methods with hands-on tutorials during the afternoons, while the second and third weeks will have lectures by international and local experts. The course has a strong hands-on component based on student proposed modeling or data analysis projects, which are further refined with the help of a dedicated tutor. Applicants are required to propose their project at the time of application. There is no tuition fee. The sponsor will provide lodging and meals during the course and may provide partial travel support. We hope that this course will be a good opportunity for theoretical and experimental neuroscientists to meet each other and to explore the attractive nature and culture of Okinawa, the southernmost island prefecture of Japan. Invited faculty: • Upinder Bhalla (NCBS, India) • Claudia Clopath (Imperial College London, UK) • Erik De Schutter (OIST) • Tomoki Fukai (OIST) • Yukiko Goda (OIST) • Mike Häusser (University College London, UK) • Bernd Kuhn (OIST) • Jinny Kim (KIST, South Korea) • Sam Reiter (OIST) • Greg Stephens (OIST) • Kazumasa Tanaka (OIST) • Marylka Yoe Uusisaari (OIST) • more to be announced

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6 PhD positions available in biomimetic embodied AI
by Thomas Nowotny Dec. 7, 2022

Dec. 7, 2022

Dear Comp-Neuro community, We are offering 6 PhD studentships in our unique be.AI doctoral training centre in biomimetic embodied AI (http://www.sussex.ac.uk/ccnr/be_ai) at the University of Sussex in Brighton. Deadline: 23 February 2023 Apply online: https://www.sussex.ac.uk/study/phd/apply Full details at https://www.sussex.ac.uk/study/fees-funding/phd-funding/view/1403-Leverhulm…. Kind regards, Thomas -- Prof. Thomas Nowotny Head of AI Research Group CCNR, Sussex Neuroscience Phone: +44-1273-678593 Engineering and Informatics, Fax: +44-1273-877873 University of Sussex, Falmer, Brighton BN1 9QJ sussex.ac.uk/informatics/tnowotny<http://sussex.ac.uk/informatics/tnowotny> <../../owa/redir.aspx?C=9e11bb0e527242938402b42d9b5498ea&URL=http%3a%2f%2fsussex.ac.uk%2finformatics%2ftnowotny> I support the University of Sussex Community Pledge, as I continue to help those around me during the pandemic. Small acts of collaboration, kindness and integrity can make a big difference. www.sussex.ac.uk/community-pledge<http://www.sussex.ac.uk/community-pledge>

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PhD on neural modelling of conscious perception
by Howard Bowman Dec. 7, 2022

Dec. 7, 2022

PhD position, University of Birmingham: Identifying the Role of Conscious Perception, a Neuroimaging and Computational Investigation Howard Bowman and Damian Cruse, School of Psychology, University of Birmingham are seeking applications for this PhD project, which is competition-funded under the Midlands Integrative Biosciences Training Partnership (supported by the UK Biotechnology and Biological Sciences Research Council). The deadline for applications is Friday, January 20, 2023; a percentage of the available scholarships can be allocated to non-UK students. Informal enquires can be made to H.Bowman(a)kent.ac.uk<mailto:H.Bowman@kent.ac.uk>. The question of what conscious perception is for remains a key issue for science. In fact, a substantial part of the scientific study of consciousness has focused on showing how sophisticated subconscious processing can be, seemingly leaving little room for a "special" purpose for conscious experience. We have recently presented evidence that the subconscious brain is limited in its capacity to represent episodic information (Avilés, Bowman & Wyble, 2020; Bowman & Avilés, In Press; Bowman et al, 2014). We now have extensive behavioural evidence for this hypothesis. We are thus at a perfect stage to 1) characterise the neural correlates (with fMRI, MEG or EEG) that support this formation of episodic memories, and 2) explain these findings with the Simultaneous Type/ Serial Token (STST) model (Bowman & Wyble, 2007), a neural network model of temporal attention. We are proposing a PhD to work on one or both of these topics. More details can be found at, https://warwick.ac.uk/fac/cross_fac/mibtp/pgstudy/phd_opportunities/neurosc… https://warwick.ac.uk/fac/cross_fac/mibtp/ -------------------------------------------- Professor Howard Bowman (PhD) Professor of Cognition & Logic in Computing at Uni Kent, and Professor of Cognitive Neuroscience in Psychology at Uni Birmingham (honorary at Wellcome Centre for Human Neuroimaging, University College London) Centre for Cognitive Neuroscience and Cognitive Systems and the School of Computing, University of Kent at Canterbury, Canterbury, Kent, CT2 7NF, UK email: H.Bowman(a)kent.ac.uk<mailto:H.Bowman@kent.ac.uk> WWW: http://www.cs.kent.ac.uk/people/staff/hb5/ School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK

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Call for community review: The Essential Metadata for 3D BRAIN Microscopy metadata standards (3D-MMS)
by INCF Dec. 7, 2022

Dec. 7, 2022

*INCF seeks community feedback on the 3D Microscopy Metadata Standard (3D-MMS)* Recent advances in fluorescence microscopy techniques and tissue clearing, labeling, and staining provide unprecedented opportunities to investigate brain structure and function, and to catalog brain cell types and define their location, morphology, and connectivity in a native context. It is essential to establish and adopt standards for annotating, reporting, and formatting imaging datasets so that other researchers can understand, reuse, and integrate microscopy data. The Essential Metadata for 3D BRAIN Microscopy metadata standards (3D-MMS) were built on existing efforts and developed with input from the brain microscopy community to promote adoption. The metadata standards include 91 fields organized into seven categories: Contributors, Funders, Publication, Instrument, Dataset, Specimen, and Image. Each metadata field is specified by a name, definition, a list of allowable values, whether it is required, and the number of times it can be repeated for a dataset. These metadata standards were developed by the BRAIN 3D Microscopy Working Group, and are being implemented within the Brain Image Library, the designated repository to accept and make microscopy data publicly available for investigators funded by the US BRAIN Initiative. Comments on this standard are open until February 3, 2023. Add your comments here: bit.ly/ComRevDec22 Why is it important to comment? Community feedback on standards & best practices helps us identify how standards can be improved to be as interoperable as possible with the systems, software, and resources that are currently being used in the field. Find out how to submit your feedback: bit.ly/INCFreview You can comment to express your support, help us identify potential weaknesses, or highlight possibilities for making the standard better or more useful. We value all feedback! Read the INCF criteria for endorsement: bit.ly/INCFreviewcriteria Community review report: bit.ly/ComRevDec22 3D-MMS in the INCF SBP catalog: bit.ly/INCFsbpBRAIN Project page: bit.ly/DORyProject 3D-MMS on Github: bit.ly/3DMMSonGH 3D-MM in Nature: go.nature.com/3VWdcWX Thanks for your help! /The INCF Team

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Postdoc on Brain network mechanisms underlying spatial cognition
by Peter Dayan Dec. 7, 2022

Dec. 7, 2022

Postdoc position (m/w/d): Brain network mechanisms underlying spatial cognition A postdoc position is available at the Department of Computational Neuroscience at the Max Planck Institute for Biological Cybernetics to work with Dr. Oxana Eschenko on brain network mechanisms underlying spatial cognition. This project is a follow up study (Yang; https://www.jneurosci.org/content/jneuro/39/3/434.full.pdf; Mei; http://learnmem.cshlp.org/content/25/3/129) aiming at understanding the role of two thalamic nuclei – the nucleus reuniens and mediodorsal nucleus - within a large-scale brain network underlying spatial cognition. The involvement of both thalamic nuclei in spatial cognition can be inferred from anatomical connectivity and neuropharmacology, while neurophysiological mechanisms of the spatial network dynamics remain poorly understood. We hypothesize that a functional coupling exists between the associative thalamic nuclei, the hippocampus, and the prefrontal cortex and that this coupling enables successful spatial navigation and retrieval of spatial memory. To test this hypothesis, we recorded multi-site neural activity while rats learned a complex maze task, and plan to relate model-agnostic and model-dependent behavioral variables reflecting learning and decision-making to aspects of the extracellular neural signals, including spectral decomposition, coherence, cross-frequency and phase-amplitude analysis. Candidates should have strong computational and data science skills and proven experience in the analysis of behavior and neural signals. Proficiency in English is essential. The position is available from March 1, 2023 and will be for one year in the first instance, subject to a probationary period. An extension may be possible depending on performance. Remuneration is based on qualifications and professional experience in accordance with the collective agreement for the public service (TVöD Bund) plus various social benefits and additional pension provision. The Max Planck Society is an equal opportunity employer: Handicapped individuals are strongly encouraged to apply, and so are women in areas in which they are underrepresented. The Max Planck Society strives for gender and diversity equality. We welcome applications from all backgrounds. Please contact Dr. Eschenko (e-mail: oxana.eschenko(a)tue.mpg.de) with any enquiries. Application deadline is January 31, 2023. Please upload your application documents electronically to our job portal by Jan 31, 2023 using the following link: https://jobs.tue.mpg.de/jobs/191

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Postdoc position in deep learning, closed loop methods, and explainable ML at Cold Spring Harbor Laboratory
by Benjamin Cowley Dec. 6, 2022

Dec. 6, 2022

A postdoctoral position in computational neuroscience /machine learning is available in Dr. Benjamin Cowley’s research group at Cold Spring Harbor Laboratory, NY. We are looking for a computational postdoc broadly interested in using machine learning approaches to answer scientific questions about the brain. We focus on designing *closed-loop methods for systems neuroscience* as well as building *explainable computational models of neural responses and behavior*. An important component of our work is to build tight-knit collaborations with experimental neuroscientists—collecting data and building models in tandem. A long-term goal is to identify and understand the step-by-step computations in the brain. For more information, see cowleygroup.cshl.edu Position Requirements Qualifications: PhD in machine learning, computer science, statistics, engineering, neuroscience, or related field; strong programming skills, publications in machine learning conferences or neuroscience journals, and experience or interest in neuroscience and collaborating with experimentalists. Familiarity with deep learning is recommended but not needed. To apply: Interested candidates should Please submit a CV, a short description of how our research interests overlap, and contact information for two references to: cowley(a)cshl.edu. In addition, please apply via the CSHL careers website at: https://cshl.peopleadmin.com/postings/20312 Position ID 03327-R. Candidates from non-traditional and/or underrepresented backgrounds, broadly defined, are strongly encouraged to apply. Environment Cold Spring Harbor Laboratory is a world-renowned biomedical research institution in New York. It has shaped contemporary biomedical research and is the home of eight Nobel Prize laureates. Cold Spring Harbor Laboratory provides a highly dynamic and interactive research environment and also a unique opportunity of timely exposure to advances in various biomedical research fields and of interaction with a broad range of researchers from all over the world through its renowned Meetings and Courses program. We believe that science is for everyone. We have had researchers with a variety of backgrounds and believe in the importance of diversity, equity, and inclusion. Compensation and Benefits Our employees are compensated from a total rewards perspective in many ways for their contributions to our mission, including competitive pay, exceptional health benefits, retirement plans, paid time off, and a range of recognition and wellness programs. Visit our CSHL Benefits & Postdoctoral Landing sites to learn more.

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Funded PhD position available in Cellular Modelling
by b.flanagan＠ulster.ac.uk Dec. 5, 2022

Dec. 5, 2022

The Intelligent Systems Research Centre at Ulster University is advertising a funded PhD position for a project titled “Computational Biophysical Modelling of Motor Neuron Disease.” Within this PhD, the candidate will explore several different disciplines including neuroscience, physics, and cell biology to develop a computational biophysical model which will help our understanding of the pathway to MN death in ALS. The candidate will consider the environment of the MN neurons, including glutamate pathways, surrounding astrocytes and the movement of ions, integral to proper neuronal function. The candidate will work closely with experimental neuroscientists to validate their model in vitro, to help further our understanding of the disease and offer insights into treatment development. More details about this position are available at https://www.ulster.ac.uk/doctoralcollege/find-a-phd/1455693. The PhD candidate will be based at the Derry campus of Ulster University, rated in the UK’s Top Ten Research Schools. Derry is located on the banks of the River Foyle in the north-west of Northern Ireland, perfectly positioned between the dramatic scenery of the Wild Atlantic Way and the Causeway Coast. It is a vibrant city seeped in history and culture, and its multitude of family-friendly activities makes Derry a great place to live. For more information, visit https://www.visitderry.com/ Essential criteria: Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study. We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction. In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications. Experience using research methods or other approaches relevant to the subject domain. A comprehensive and articulate personal statement. Desirable Criteria If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview. First Class Honours (1st) Degree Masters at 70% For VCRS Awards, Masters at 75% Experience using research methods or other approaches relevant to the subject domain Work experience relevant to the proposed project Publications - peer-reviewed Experience of presentation of research findings Please contact Bronac (b.flanagan(a)ulster.ac.uk) if you are interested or have questions. --

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My Seizure Gauge Seizure Forecasting Challenge
by Levin Kuhlmann Dec. 4, 2022

Dec. 4, 2022

The 'My Seizure Gauge Seizure Forecasting Challenge' is now open from Dec 1 2022 until March 1 2023. The contest is hosted on Eval.ai and has a total prize pool of $USD 16,000. The goal is to develop seizure forecasting algorithms using wearables data. More details are available at the following link https://eval.ai/web/challenges/challenge-page/1693/overview The contest is supported by the Epilepsy Foundation of America, Seer Medical, The Mayo Clinic, Kings College London, The University of Freiburg and Monash University. -- Cheers, Levin Kuhlmann, PhD Senior Lecturer of Data Science, AI and Digital Health Director of Master of AI Faculty of Information Technology Monash University Rm 2.73, Woodside Building, Clayton Campus email: levin.kuhlmann(a)monash.edu phone: +61412 552283 web: https://research.monash.edu/en/persons/levin-kuhlmann

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Postdoc in computational neuroscience at NYU
by Cristina Savin Dec. 2, 2022

Dec. 2, 2022

Applications are invited for a postdoctoral scholar position in the Savin and Angelaki group in the Centre for Neural Science at NYU. The position is funded by a new NIH grant, and focuses on elucidating the mechanisms of spatial navigation using multi-area recordings in freely moving monkeys in the context of foraging tasks. Aspects of this problem include determining the mechanisms representing and updating beliefs about location of self and targets, through the lens of interaction between multiple cortical areas. A significant component of the work focuses on developing new statistical data analysis tools for understanding inter-area communication in the context of naturalistic behavior. This is a joint endeavor across the two lab, with weekly joint meetings and regular group interactions. More broadly, the postdoc will be part of a large and intellectually vibrant community of researchers from the Center for Neuroscience and the Centre for Data Science at NYU. The initial appointment is one year with the expectation of extension contingent on satisfactory progress. The successful applicant will have a degree in computational neuroscience or machine learning, excellent coding skills (python) and a track record of successful research. Prior experience in neural data analysis, probabilistic machine learning, or open software development are particularly appreciated. Prior experience in neuroscience is welcome, but not strictly required. Finally, since this is a highly interdisciplinary and collaborative project, good communication skills are important. Please submit your application to csavin(a)nyu.edu <mailto:csavin@nyu.edu>, including - CV - a statement of research interests - contact details of three people that are familiar with your work We will be evaluating the applications on a rolling basis, starting from Dec 15, 2022, until the position is filled. Cristina Savin Assist.Prof. Neural Science and Data Science New York University

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Fwd: Postdoctoral position in neural coding, UKE, Hamburg (Germany)
by Stefano Panzeri Dec. 2, 2022

Dec. 2, 2022

I am seeking candidates for a fully funded postdoctoral position in computational neuroscience at the University Medical Center Hamburg-Eppendorf (UKE). The successful candidate will conduct research in my computational laboratory (Department of Excellence for Neural Information Processing) at UKE ( https://www.uke.de/english/departments-institutes/institutes/department-of-…) in collaboration with my lab’s experimental collaborators, including prominently Prof. Christopher Harvey at Harvard Medical School, Prof. Tommaso Fellin at IIT Italy, and Prof. Mriganka Sur at MIT. We will investigate, by developing and using advanced data analysis methods and biophysically plausible neural network models, how populations of neurons (and of glia) in the brain encode information and use it to produce appropriate behaviors. We are particularly interested in discovering how correlations between neurons shape the encoding and transmission of information across areas of the cerebral cortex, and in understanding the theoretical principles of how to combine measures and perturbations of neural activity to probe causally the contributions of interactions between neurons to brain function. Our laboratory offers a wide range of interdisciplinary expertise in computational neuroscience, including both advanced neural analysis techniques and neural network modeling. The laboratory also offers a thriving, ambitious and well-funded research environment (including receiving funding from the NIH Brain Initiative, Simons Foundation, the European Union). This gives successful candidates ample opportunities for advanced training and personal scientific growth. We seek candidates holding a PhD in a numerate or neuroscientific discipline, with a solid computational background and a keen interest in neuroscience. They must be highly motivated and creative individuals who want to work in a dynamic, multi-disciplinary research environment and be willing to interact with both experimental and theoretical neuroscientists. The job is available starting immediately and applications will be considered as soon as they are received and until the position is filled. Funding is available for several years and a minimum commitment of two years is expected by interested candidates. Interested applicants are strongly encouraged to email me (s.panzeri(a)uke.de or stefano.panzeri(a)gmail.com) as soon as possible, to inform me of the interest for the position and initiate a discussion about research projects. I suggest interested candidates to attach a CV when inquiring by email. For recent publications from my lab relevant to this project, see: Panzeri S, et al (2022) The structures and functions of correlations in neural population codes. *Nature Reviews Neuroscience* 23: 551-567 Koren V., Panzeri S (2022) Biologically plausible solutions for spiking networks with efficient coding. *NeurIPS 2022,* in press, arXiv:2210.07069 Curreli S, et al (2022) Complementary encoding of spatial information in hippocampal astrocites. *PLoS Biology* 20(3): e3001530. Valente, M. et al (2021), Correlations enhance the behavioral readout of neural population activity in association cortex. *Nature Neuroscience*, 24, 975–986 Chong, E. et al (2020) Manipulating synthetic optogenetic odors reveals the coding logic of olfactory perception. *Science* 368, 1329. Runyan C. A., et al (2017) Distinct timescales of population coding across cortex, *Nature*: 548: 92-96. Panzeri S., et al (2017) Cracking the neural code for sensory perception by combining statistics, intervention and behaviour. *Neuron* 93: 491-507 Pica, G. et al (2017) Quantifying how much sensory information in a neural code is relevant for behavior, *Neural Information Processing Systems (NeurIPS 2017)* Thanks Stefano Panzeri

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Post-doc and graduate positions in DeAngelis lab, with Moreno-Bote and Drugowitsch Labs
by Ruben Moreno Bote Dec. 2, 2022

Dec. 2, 2022

Postdoctoral and PhD positions in systems neuroscience, DeAngelis Lab, University of Rochester, in collaboration with Moreno-Bote and Drugowitsch Labs. A postdoctoral position and a graduate student assistantship in Systems Neuroscience are available at the University of Rochester, in the laboratory of Dr. Greg DeAngelis. The positions are part of a recently funded NIH project on the neural mechanisms of visually-guided navigation in virtual reality. The project is a collaboration with the laboratories of Dr. Ruben Moreno-Bote (UPF, Barcelona) and Dr. Jan Drugowitsch (Harvard Medical School, Boston). A 1-month visit to Barcelona every year is expected to foster the collaborative aspects of the project. The project involves psychophysics and large-scale electrophysiology in non-human primates, combined with computational approaches. The goal is to elucidate neural mechanisms for the visual-motor control of steering. Successful candidates will join a highly dynamic and collaborative group at the Center for Visual Science (https://www.cvs.rochester.edu) with strong theoretical/computational collaborations with the laboratories of Moreno-Bote and Drugowitsch, and expected extended visits to their labs. Previous work from our group has made fundamental contributions to our understanding of the neural basis of motion perception, depth perception, multisensory integration, self-motion perception, and perceptual decision-making ( https://pubmed.ncbi.nlm.nih.gov/?term=deangelis_gc&sort=date&size=100) Candidates are expected to have a background in neuroscience, experimental psychology, biomedical engineering, or a related field. Previous research experience in systems neuroscience is desirable, although it is not necessary. Candidates should submit their CV, a brief statement of research interests, and the names and contact information for three references to gdeangelis(a)ur.rochester.edu. -- Rubén Moreno Bote Serra Húnter Professor Director of the Theoretical and Cognitive Neuroscience Group Center for Brain and Cognition & Dept. of Information and Communications Technologies University Pompeu Fabra Campus Ciutadella c\ Ramon Trias Fargas, 25-27 Mercè Rodoreda building, 3th floor (room 24.331) 08005 Barcelona, Spain https://www.upf.edu/web/tcn https://twitter.com/morenobote <https://twitter.com/morenobote?lang=ca>

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PhD modelling brain learning
by O'Donnell, Cian Dec. 2, 2022

Dec. 2, 2022

Our group at Ulster University are looking for a computational neuroscience PhD student for a project on “Discovering the rules of neural learning by computer simulations of brain biophysics and deep neural networks.” You will use multiscale computer simulations of electro-chemical signalling in neurons, synapses, and astrocytes to understand how the physical arrangement of different cell types affects brain learning. You can then use more abstract deep neural network models to study the circuit functions of these mechanisms for learning and memory. More details including reading material here: https://www.ulster.ac.uk/doctoralcollege/find-a-phd/1455716. The project will involve collaboration with Tom Bartol at the Salk Institute, La Jolla, California. You will join our research group which uses computational tools to do research on synaptic plasticity, learning and memory, autism, and neural data analysis methods: https://odonnellgroup.github.io. You will also be a member of the CNET team in the Intelligent Systems Research Centre (http://isrc.ulster.ac.uk) a community of researchers working across computational and cognitive neuroscience, neurotechnology, neuromorphic engineering, machine learning, robotics and related fields. We are based in the Derry campus of Ulster University. Derry a lively city of ~100K people on the River Foyle in Northern Ireland, UK. It has a highly affordable cost of living, thriving cultural scene, and access to spectacular coastal scenery and the great outdoors in Donegal and the north coast of Northern Ireland. To be eligible for funding, UK-based applicants should have or expect to obtain an upper second or first-class undergraduate or masters degree. International applicants should have a masters degree. Application deadline is 27th February 2023, for a Sept 2023 start. Application info here: https://www.ulster.ac.uk/doctoralcollege/find-a-phd/1455716. Please contact Cian (c.odonnell2(a)ulster.ac.uk<mailto:c.odonnell2@ulster.ac.uk>) if you are interested or have questions. -- Cian O’Donnell Lecturer in Data Analytics School of Computing, Engineering and Intelligent Systems Ulster University https://odonnellgroup.github.io 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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Kempner Institute Fellowships at Harvard University
by Cengiz Pehlevan Dec. 1, 2022

Dec. 1, 2022

The Kempner Institute at Harvard University is soliciting applications for the Kempner Institute Fellowships. We seek candidates with demonstrated ability and creativity who study one or more of the following areas: Foundations of intelligence, including mathematical and computational models of intelligence, cognitive theories of intelligence, computational neurobiology, and the neurobiological basis of intelligence. Applications of artificial intelligence, including natural language processing, visual scene processing and analysis, and to the mechanistic analysis of high dimensional neural and behavioral data. The study of these applications can either be from an engineering standpoint (e.g. development of new methodologies or advancing the state of the art) as well as from a scientific one (e.g. achieving a better understanding of deep learning). The Fellowship is intended for early stage scientists and will provide them with opportunities for intellectual growth in a highly interdisciplinary and collaborative environment. The fellows will independently set their research agenda but are strongly encouraged to work between fields and collaborate with preeminent experts at the Kempner Institute and at Harvard, more generally. Fellows will be appointed for a term of up to 3 years, with an annual salary of $100,000 and up to $10,000 per year of research support. Fellows will have access to shared office space, world-class computational resources and engineering support. They will benefit from a wide and deeply-engaged community of scientists, as well as access to the breadth of resources and facilities available to members of Harvard University. See https://academicpositions.harvard.edu/postings/11860 <https://academicpositions.harvard.edu/postings/11860> for more information. For other postdoctoral opportunities at Harvard for researchers in ML/AI, please see this webpage https://mlfoundations.org/#opportunities <https://urldefense.proofpoint.com/v2/url?u=https-3A__mlfoundations.org_-23o…>

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CFP: FLAIRS-36, Neural Networks and Data Mining Special Track, Clearwater Beach, Fl, May 14-17, 2023
by David B Nov. 30, 2022

Nov. 30, 2022

FLAIRS-36 Clearwater Beach, Florida, USA, May 14-17, 2023 Neural Networks and Data Mining Special Track Abstract submission deadline: February 6, 2023 Paper submission deadline: February 13, 2023 Notifications: March 13, 2023 Camera ready version due: April 10, 2023 The Florida Artificial Intelligence Research Symposium (FLAIRS) is a medium-sized interdisciplinary AI conference which is noted for its double-blind reviewing, free tutorials, and beautiful venues. This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas. Papers and contributions are encouraged for any work related to neural networks, data mining, or the intersection thereof. Topics of interest may include (but are in no way limited to): 1. Applications such as Pattern Recognition, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Telecommunications, Power Systems, Signal Processing; Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy. 2. Algorithms such as new developments in Back Propagation, SVM, Deep Learning, Ensemble Methods, Kernel Approaches; hybrid approaches such as Neural Networks/Genetic Algorithms, Neural Network/Expert Systems, Causal Nets trained with Backpropagation, and Neural Network/Fuzzy Logic. 3. Modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches. 4. Graph modeling, pattern discovery, and anomaly detection. 5. Feature extraction and selection. 6. Post-processing techniques such as visualization, summarization, or trending. 7. Preprocessing and data reduction. 8. Knowledge engineering or warehousing. Papers dealing with Cloud-based unstructured data or tool suites, such as TensorFlow, PyTorch, Mahout, or Apache Spark, are also encouraged. Submission Guidelines Submitted papers must be original, and not submitted concurrently to a journal or another conference. Double-blind reviewing will be provided, so submitted papers must use fake author names and affiliations. Papers must follow the FLAIRS template guidelines ( https://www.flairs-36.info/call-for-papers) and be submitted as a PDF through the EasyChair conference system. (Do NOT use a fake name for your EasyChair login; your EasyChair account information is hidden from reviewers.) FLAIRS will not accept any paper which, at the time of submission, is under review for or has already been published or accepted for publication in a journal or another conference. Authors are also required not to submit their papers elsewhere during FLAIRS's review period. These restrictions apply only to journals and conferences, not to workshops and similar specialized presentations with a limited audience and without archival proceedings. Authors will be required to confirm that their submissions conform to these requirements at the time of submission. Conference Proceedings Papers will be refereed and all accepted papers will appear in the conference proceedings. Program committee: Track Co-Chairs: David Bisant, Central Security Svcs, bisant(a)umbc.edu Steven Gutstein, Army Research Laboratory, s.m.gutstein(a)gmail.com William Eberle, Tennessee Tech University, weberle(a)tntech.edu Program Committee Members: Martin Atzmueller (University of Kassel, Germany) Juan Banda (Montana State University, USA) Lori Bogren (Verizon Business Solutions, USA) Sergei Dolenko (D.V.Skobeltsyn Inst of Nuc Phys, M.V.Lomonosov Moscow St Univ) Yoni Fridman (Verizon Business Solutions, USA) Olac Fuentes (University of Texas at El Paso, USA) Hyoil Han (Marshall University, USA) Sheikh Rabiul Islam (University of Hartford, USA) Mike James (iProgrammer, United Kingdom) Jacek Kukluk (Dana-Farber/Harvard Cancer Center, USA) Katrina Kutchko (Verizon Business Solutions, USA) Prabin Lamichhane (Mastercard, USA) Lenin Mookiah (eBay, USA) Ramesh Paudel (George Washington University, USA) Roberto Santana (University of Basque Country, Spain) Hujun Yin (University of Manchester, UK) Further Information Questions regarding the Data Mining Special Track should be addressed to the track co-chairs: David Bisant, Central Security Svcs, bisant(a)umbc.edu Steven Gutstein, Army Research Laboratory, s.m.gutstein(a)gmail.com William Eberle, Tennessee Tech University, weberle(a)tntech.edu Invited Speakers To be announced Conference Web Sites Paper submission site: https://www.flairs-36.info/submissions FLAIRS-36 conference web page: https://www.flairs-36.info/ Florida AI Research Society (FLAIRS): https://www.flairs.com

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