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Assistant professor position in Göttingen, Germany
by Ecker, Alexander June 21, 2021

June 21, 2021

We have an opening for an assistant professor position for ML/CV for biomedical applications in the computer science department at the University of Göttingen, Germany. Application deadline it July 11. For details see below or at https://www.uni-goettingen.de/en/645470.html The Faculty of Mathematics and Computer Science at the Georg-August-University of Goettingen invites applications for a Sartorius AG Endowed Junior Professorship W1 – „Computational Cell Analytics“ (all genders welcome) The junior professorship will be part of the "CIDAS-Sartorius lab for AI-based high-throughput analysis of cell systems" and will actively contribute to its further development. In the CIDAS-Sartorius Lab, we will develop novel data analysis methods to obtain scientific insights from observations of cell systems in various areas of the life sciences. It is a collaboration between the Campus Institute Data Science (CIDAS), the Institute for Computer Science, the University Medical Center Goettingen and Sartorius AG. The junior professorship will also be part of the Campus Institute Data Science (CIDAS) and contribute to its development. CIDAS is a central institution of the University of Goettingen and works closely with the partners of the Goettingen Campus such as the University Medical Center, several Max Planck Institutes, the German Primate Center, the Academy of Sciences and the German Aerospace Center Goettingen. The junior professorship is thus optimally integrated into Goettingen's top-notch life science research environment. The future holder of the position should have expertise in computer science with a focus on machine learning/deep learning and/or computer vision. The professorship contributes to the development of new analytical methods and their application in the field of cell analysis. Possible research foci are among others: - Computer vision in biomedical imaging - Biomedical image processing - Image based cell and biomolecular analytics - Methods for object recognition and image segmentation - Large-scale machine learning & deep learning - Nonlinear and dynamic prognosis models for the description and prediction of complex, nonlinear processes in cell models The candidate should have a track record of internationally competitive high-quality research and a high potential for groundbreaking research in internationally visible projects. The candidate is expected to contribute to teaching in the data science programs. Goettingen University is committed to research-oriented teaching. Applications of international scientists are highly encouraged. The University is an equal opportunity and family friendly employer. We specifically encourage women to apply. Disabled persons with appropriate qualifications and aptitude for the position will be given special consideration. Applications including CV, publications list and details of teaching and research including funded research projects should be submitted by 11 July 2021 online via the application portal: https://tinyurl.com/44r336yn For further information please contact Prof. Dr. Alexander Ecker, Institute of Computer Science and Campus Institute Data Science: ecker(a)cs.uni-goettingen.de. -- Alexander Ecker Professor of Data Science Department of Computer Science • Campus Institute Data Science University of Göttingen • Max Planck Inst. for Dynamics and Self-Organization Goldschmidtstr. 1 • room 2.137 • 37077 Göttingen https://eckerlab.org • @alxecker • +49 551 39-21272

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PhD Studentship in Improving medication verification for cancer patients
by Shangming Zhou June 20, 2021

June 20, 2021

Dear All, *PhD Studentship in Improving medication verification for cancer patients: An AI driven population health study* Applications are invited for a three-year PhD studentship. The studentship will start on* 1 October, 2021, *or as soon as possible after that. *Overview of the Studentship* This fully funded PhD studentship is based at the University of Plymouth’s Centre for Health Technology <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…>, a leading international research group focused on the design, development and implementation of health technology innovations in health and care. This vibrant team of researchers work within the intersection of digital health, software engineering, data science, clinical artificial intelligence, and innovation strategy, with a primary aim to create a global hub for technology incubation in the South West of the United Kingdom. *Project Description* Medication errors, including those in prescribing, dispensing, or administration of a drug, are the single most preventable cause of patient harm. They have a significant impact on the efficiency of the workflow in pharmacy, raise safety concerns for patients, and result in a financial burden on the healthcare systems. Within cancer treatment, emphasis on reducing the number of medication errors has been an active research area for many years, with understanding that interdisciplinary approaches are vital to assure continuous improvement. Opportunities created by the reduction of transaction times for complex computational processes and use of machine learning to support clinical decision making, create a potential catalyst for the development of tools for reduction in medication errors. This PhD studentship offers an exciting opportunity of exploring AI and machine learning with large clinical data sets residing within electronic health records to create methods to assure the effective use of systemic anticancer treatment (including traditional cytotoxic chemotherapy, immunotherapy, novel oral therapies etc.) without compromising patient safety. The studentship will require application of interdisciplinary skills to enable cooperation between the research, clinical, industry and patient communities in the development of a novel approach which could enhance clinical outcomes. *Supervision Team* - Professor Shang-Ming Zhou <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…> (shangming.zhou(a)plymouth.ac.uk) https://scholar.google.com/citations?user=iWiXGWMAAAAJ&hl <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fscholar.g…> - Dr Edward Meinert (edward.meinert(a)plymouth.ac.uk) https://scholar.google.com/citations?hl=en&user=7V-WsrwAAAAJ <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fscholar.g…> - Mrs Andrea Preston (Andrea.Preston(a)uhbw.nhs.uk) This PhD student will be academically advised by Professor Shang-Ming Zhou and Dr Edward Meinert, research scientists with research interests in applied artificial intelligence and machine learning, computing science in health and care. The student will also be advised by Mrs Andrea Preston, a Macmillan Divisional Lead Haematology & SW Cancer Commissioning Pharmacist. This supervision team will assure the execution of a world-class PhD embedded into the wider digital health ecosystem at the University of Plymouth. *Eligibility* · This PhD studentship is offered for UK and international applicants. · Applicants should have: 1) A first or upper second-class honours degree, and a relevant Master’s qualification in Computing Science, Data Science, Statistics, Health Informatics, Medical Informatics, Bioinformatics, or any areas related; 2) Interest in working with real-world problems and large data sets; 3) Excellent proficiency in English and outstanding communication skills; 4) Strong analytical and programming skills; 5) A “can do”, positive attitude with an aspiration to change the world. · Experience in machine learning is advantageous. · Experience in publication of peer-reviewed literature is desirable. *International Students* International applicants should meet the English language requirements, please see the details from the University’s website https://www.plymouth.ac.uk/international/how-to-apply/english-language-requ… <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…>. IELTS Academic 6.5 or above (or equivalent) with 5.5 in each individual category is commonly required by the University’s Doctoral College. *How to Apply* *To apply for this position,* please visit: https://www.plymouth.ac.uk/student-life/your-studies/research-degrees/postg… <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…>. *Please clearly state the name of the studentship that you are applying for on your Personal Statement.* A research proposal is required. Please see: https://www.plymouth.ac.uk/student-life/your-studies/research-degrees/appli… <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…> for a list of supporting documents to upload with your application. *Enquiry * If you wish to discuss this project further informally, please contact Professor Shang-Ming Zhou (shangming.zhou(a)plymouth.ac.uk) Dr Edward Meinert (edward.meinert(a)plymouth.ac.uk) or Mrs Andrea Preston ( Andrea.Preston(a)uhbw.nhs.uk) For more information on the admissions process, please contact doctoralcollege(a)plymouth.ac.uk. *Closing Date* *The closing date for applications is 30 July 2021. *Shortlisted candidates will be invited for interview. Best wishes Shangming Zhou _______________________________________________________ Shang-Ming Zhou Professor in e-Health, Fellow of the Higher Education Academy, Centre for Health Technology, Faculty of Health, University of Plymouth, Plymouth, PL4 8AA, UK Tel: +44 (0)1752 586513 Email: shangming.zhou(a)plymouth.ac.uk ; smzhou(a)ieee.org https://www.plymouth.ac.uk/staff/shang-ming-zhou <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…> https://www.hdruk.ac.uk/people/dr-shang-ming-zhou <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.hdruk…> https://www.plymouth.ac.uk/research/centre-for-health-technology <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.plymo…>

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BrainCosmos Summer School on Neural Circuit Complexity from Aug 30-Sep 3
by Shyam Diwakar June 19, 2021

June 19, 2021

Dear Fellow Neuroscientists and Students, We would like to welcome you to a BrainCosmos Summer School titled "Neural circuit complexity: Neuroscience, Models and Robotics - Where do they lead?" organized at Lake Como, Italy from August 30-September 3, 2021. For more info: https://brco.lakecomoschool.org/ <https://brco.lakecomoschool.org/> The BrainCosmos summer school focuses on the study of the brain, neuroscience of circuits and behavior in micro and macro scales, models, experiments, alongside topics of robotics and artificial intelligence and a perspective on brain diseases. The school primarily targets PhD students across all research disciplines, but applications from professionals, masters students and post-doctoral researchers are welcome as well. The School will also cater to early career researchers in Neuroscience and will aim to promote critical thinking within the field and beyond. The scope covers a very wide range of topics that we believe to be of interest to many fields related to neuroscience, modeling, robotics and artificial intelligence. PARTICIPATION: The school will run in parallel with two simultaneous batches, one in presence (20 participants) and another remotely (20 participants). The lectures will be streamed. APPLY: https://brco.lakecomoschool.org/application/ FEES: There are some nominal fees for participation. In presence attendance: € 120, 22% VAT included (including lunches, coffee breaks, and all lectures and school materials). Online attendance: €100, 22% VAT included (including the possibility to participate remotely to all the lectures given during the school and to the related initiatives, and to have access to the recordings of the lessons from the school portal for a period of three months after the end of the school. KEY DATES Application deadline: July 20 Acceptance notification: July 23 Registration (only accepted students): August 3 Confirmed FACULTY list: Anna Letizia Allegra Mascaro - LENS, Florence, Italy Alberto Antonietti - EPFL, Swiss Silvia Casarotto – University of Milan, Italy Claudia Casellato - University of Pavia, Italy Marco Dal Maschio – University of Padoa, Italy Egidio D'Angelo - University of Pavia, Italy Damien Depannemaecker - CNRS, Paris, France Shyam Diwakar - Amrita Mind Brain Center, Amrita University, India Kenji Doya – Okinawa Institute of Science and Technology Graduate University, Japan Claudia Gandini Wheeler-Kingshott - University College London, UK & University of Pavia, Italy Alice Geminiani - University of Pavia, Italy Michele Giugliano – SISSA, Trieste, Italy Alberto Mazzoni - Scuola Superiore Sant’Anna Pisa, Italy Michele Migliore - CNR Palermo, Italy Fulvia Palesi – BCC Pavia, Italy Alessandra Laura Giulia Pedrocchi - Politecnico Milano, Italy Michele Piana - University of Genoa, Italy Isabella Pozzi - CWI, Amsterdam Holland Simone Sarasso – University of Milan, Italy The School DIRECTORS: Giovanni Naldi - University of Milan, Department of Environmental Science and Policy, Italy. giovanni.naldi(a)unimi.it<mailto:giovanni.naldi@unimi.it> Thierry Nieus - University of Milan, Italy. thierry.nieus(a)unimi.it<mailto:thierry.nieus@unimi.it> Simone Sarasso - University of Milan, Department of Biomedical and Clinical Sciences “Luigi Sacco”, Italy. simone.sarasso(a)unimi.it<mailto:simone.sarasso@unimi.it> Shyam Diwakar - Amrita Mind Brain Center, Amrita University, India. shyam(a)amrita.edu<mailto:shyam@amrita.edu> Please feel free to circulate! With best wishes, -- Prof. Shyam Diwakar, Ph.D. Director - Amrita Mind Brain Center Faculty Fellow - Amrita Center for International Programs Amrita Vishwa Vidyapeetham (Amrita University) Amritapuri, Clappana P.O. Kollam, India. Pin: 690525 Ph:+91-476-2803116 Fax:+91-476-2899722 http://amrita.edu/mindbrain [https://docs.google.com/uc?export=download&id=1_nOxaCXob6wVcuQyYI5KVk1PhMgi…] [https://intranet.cb.amrita.edu/sig/RankingLogo.png] Disclaimer : The information transmitted in this email, including attachments, is intended only for the person(s) or entity to which it is addressed and may contain confidential and/or privileged material. Any review, retransmission, dissemination or other use of, or taking of any action in reliance upon this information by persons or entities other than the intended recipient is prohibited. Any views expressed in any message are those of the individual sender and may not necessarily reflect the views of Amrita Vishwa Vidyapeetham. If you received this in error, please contact the sender and destroy any copies of this information.

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Job: Editor with Nature Machine Intelligence (9 month locum position - London, NY, Berlin)
by Yann Sweeney June 18, 2021

June 18, 2021

Dear all, Nature Machine Intelligence are looking to recruit a locum editor. We are a new Nature Research journal that launched in 2019. It publishes both fundamental and applied research in a wide range of areas in artificial intelligence and robotics. The journal incorporates elements of computer science, electrical engineering, mathematics, physics, neuroscience, cognitive science and psychology. The journal also publishes news, commentary and perspectives on the impact of machine intelligence on science and society. We are inviting applications from those with a background in any of the above and related fields. Applicants should have completed a PhD, have a strong research record, feel driven to continually learn about new fields and trends and have a keen interest in exploring the wide implications of research on other scientific areas, industry and society. We would be interested in hearing from candidates who can demonstrate strong science writing skills. Editorial experience is not required, although applicants with significant editorial experience are encouraged to apply and will potentially be considered for a Senior Editor position. The successful candidate will report to the Chief Editor. They will participate in all aspects of the editorial process, including manuscript selection, commissioning and editing News and Views, Comments, Perspectives and Reviews, as well as writing for the journal. The successful candidate must be dynamic and outgoing, and have excellent communication and interpersonal skills. A key aspect of the job is liaising with the research community through laboratory visits and international conferences, and therefore a willingness to travel is essential. The position is offered on a full-time basis, for an initial fixed term of 9 months, and will ideally be located in our London, Berlin or New York office. The starting date is envisaged as soon as possible within the next few weeks. Full advert here, apply by 22 June: https://career5.successfactors.eu/sfcareer/jobreqcareer?jobId=33925&company… Feel free to email with informal inquiries. All the best, Yann Senior Editor Nature Machine Intelligence yann.sweeney(a)nature.com

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Postdoc opportunity at Stanford Cognitive and Systems Neuroscience Laboratory
by Mai-Phuong K Bo June 18, 2021

June 18, 2021

The Stanford Cognitive and Systems Neuroscience Laboratory (scsnl.stanford.edu<https://med.stanford.edu/scsnl.html>) invites applications for post-doctoral positions with expertise in cognitive, systems and computational neuroscience. Candidates must have a PhD and research experience in cognitive neuroscience, psychology, cognitive science, computer science, electrical/biomedical engineering, or related fields. The successful candidate will develop a vigorous research program that contributes to, and complements, ongoing research studies of human brain function and psychopathology. The candidate will have access to multiple large datasets and state-of-the-art computational resources, including HPCs and GPUs. We are especially interested in talented and highly motivated individuals with expertise in at least one of these areas: cognitive neuroscience; computational psychiatry; cognitive modeling of behavioral dynamics; computational and statistical analysis of brain imaging and electrophysiological data, including dynamic brain circuit analysis, statistical modeling and Bayesian inference, machine learning, and deep neural networks. Please email your CV and a statement of research interests, explaining how your skills and past experience will advance human neuroscience research, to Prof. Menon at scsnl.stanford+postdoc(a)gmail.com<mailto:scsnl.stanford+postdoc@gmail.com>. Mai-Phuong Bo (She/Her) Lab & Recruitment Manager Stanford Cognitive & Systems Neuroscience Lab Department of Psychiatry & Behavioral Sciences Email: maipbo(a)stanford.edu [cid:461d2e43-3a74-4692-8e70-e709a54c2c86]

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Postdoc position at Inria Sophia Antipolis
by Etienne Tanré June 17, 2021

June 17, 2021

Dear colleagues, Apologies for Cross-Posting, This is an announcement for a 24 months post-doctoral position at Inria Sophia Antipolis on the theme ``Heterogeneity in interacting neural networks'’. The candidate will be supervised by E. Tanré, R. Veltz and O.Faugeras. This project is part of the Human Brain Project HBP SGA3. More information is available on : https://jobs.inria.fr/public/classic/en/offres/2021-03818 <https://jobs.inria.fr/public/classic/en/offres/2021-03818> Please note that you must apply for the position using the link above. Can you please forward this announcement to your interested contacts? Thank you, Best regards, E. Tanré, R. Veltz and O. Faugeras.

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Opening: Postdoctoral Researcher in Computational Neuroscience to study network dynamics, brain function, and psychedelics
by Joern Davidsen June 16, 2021

June 16, 2021

Dear all: We are recruiting a talented postdoctoral researcher to participate in a cutting-edge International Network for Brain-Inspired Computation<https://www.nsf.gov/awardsearch/showAward?AWD_ID=2019976&HistoricalAwards=f…> that includes nodes in Montreal, Paris, and the Pacific Northwest of the US and Canada (e.g. University of Washington, Allen Brain Institute). The project is at the intersection of mathematics, physics, and neuroscience in the general area of complex network dynamics and emergent activity patterns and representations that drive biological computation. The specific objective is to understand cognitive brain function and the effects of psychedelics by analyzing large-scale ensemble neural data collected in our labs, in conjunction with computational and/or analytical work to identify key mathematical principles and develop theories of core function. The ideal candidate will have a quantitative background (e.g. PhD in mathematics, physics, computer science) along with experience in applying this background to neuroscience. This postdoctoral position is partially funded by the Pacific Institute for Mathematical Sciences<https://www.pims.math.ca/> and is aimed to strengthen the link between the Campus Alberta computational neuroscience community at the University of Calgary (Complexity Science Group<https://www.ucalgary.ca/complexity/>, Hotchkiss Brain Institute<https://hbi.ucalgary.ca/>) and the University of Lethbridge (Canadian Center for Behavioural Neuroscience<https://www.uleth.ca/artsci/neuroscience/about>) with the other network members including the Computational Neuroscience Center<https://cneuro-web01.s.uw.edu/> at the University of Washington. The position is open immediately with primary locations in either Calgary or Lethbridge. The specific start date has to be within five years of being awarded a PhD degree. The position is funded for at least two years and includes an annual stipend in the range of CAD$42,000 – $50,000 plus benefits. Opportunities for brief residences in partner nodes (Montreal, Seattle, or Paris) are also available. Interested candidates should submit their application package including a cover letter, their CV with a list of publications, brief statement of research interests and their possible start dates in PDF format to Dr. Jörn Davidsen (davidsen(a)phas.ucalgary.ca<mailto:davidsen@phas.ucalgary.ca>) and Dr. Aaron Gruber (aaron.gruber(a)uleth.ca<mailto:aaron.gruber@uleth.ca>). Applicants should arrange for at least two letters of reference to be sent as well. Review of applications will begin July 31st, 2021, and continue until the position is filled. For additional information and informal inquiries, please contact Dr. Davidsen or Dr. Gruber. We strive for a diverse and inclusive environment, and encourage applications from members of any identity. --- Dr. Jörn Davidsen Professor of Physics & Humboldt Research Fellow University of Calgary www.ucalgary.ca/davidsen<http://www.ucalgary.ca/davidsen>

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PostDoc position in Neuroinformatics, Nijmegen, The Netherlands
by Rembrandt Bakker June 16, 2021

June 16, 2021

(apologies for any cross-postings) The FLAG-ERA project NeuronsReunited is looking for a postdoctoral research associate (Neuroinformatics/Computational Neuroscience) for a 2 year position at 0.9 fte. Each mental event or voluntary motor act involves the coordinated activity of neurons in areas of the brain far apart. Thin, branched and extremely long cellular processes called axons provide the physical substrate of these interactions. Since a few years it is possible to fully trace these long- range axons one at a time. The goal of the FlagERA research project "NeuronsReunited" (https://www.flagera.eu/wp-content/uploads/2020/06/FLAG-ERA_JTC2019_HBP_Neur…) is to create tools for speeding up the conversion of experimental data into digital axons, and to precisely place neurons into a digital reference brain to reveal their context. The tools are applied to existing and new data in mouse, and the resulting insights are incorporated into new models for brain function. The project is a collaboration between five international partners, two experimental partners (Prof. Francisco Clasca, Madrid; Prof. Egidio d'Angelo, Pavia) and three computational/theoretical partners (Prof. Paul Tiesinga, Dr. Rembrandt Bakker, Nijmegen; Prof. Michele Giugliano, Trieste; Prof. Sacha Van Albada, Jülich). As a postdoctoral research associate you will design strategies to get axonal arbors precisely registered in a brain atlas. The brain atlas consists of high-resolution 3d dataset that represents the average mouse brain anatomy, while the neuron consists of a vector representation of its morphology that can be extended with images of selected tissue sections. Depending on your field of expertise, further steps can focus on automating the process to trace neurons from stained tissue sections or to integrate the resulting database of precisely registered neurons with other data modalities to generate new knowledge. You will be part of a team that deals with atlasing and data integration (Nijmegen) and model building (Jülich, Padova, Trieste). A key deliverable will be the creation of a gold standard online catalog of precisely placed neurons that future generations of neuroscientists can contribute to and compare data to. The tools make use of an existing body of work that consists of web-based applications: HBP Morphology Viewer (https://neuroinformatics.nl/HBP/morphology-viewer) Scalable Brain Atlas (https://scalablebrainatlas.incf.org/) and interactive notebooks (Python). Besides being a member of the project team, you will also be part of the European Human Brain Project and have access to the expertise of the large neuroscience community at the Donders Institute for Brain, Cognition and Behavior. We ask: • A PhD degree in a quantitative field (engineering, physics, computational neuroscience, etc). • Expertise in neuroscience or interest in acquiring it. • Excellent programming skills, preferably in JavaScript applications or Python-based pipelines. • Experience with neuroinformatics, visualization/3d-graphics, image processing, and/or machine learning. • Demonstrated ability to work in a multidisciplinary environment at the forefront of science. • Excellent communication skills in spoken and written English. We are: The Donders Institute for Brain, Cognition and Behaviour, home to more than 600 researchers from 35 countries, is a world-class research centre devoted to understanding the mechanistic underpinnings of human cognition and behaviour in health and disease. The institute's mission includes conducting excellent interdisciplinary research at the unique interface between genetic, molecular and cellular processes at one end and computational, system-level neuroscience with cognitive and behavioural analysis at the other end. Within this playing field, the Neuroinformatics department plays an essential role in developing new approaches for both computational modeling and data processing, all with the aim to turn raw data into highly valuable and well-integrated resources from which neuro-scientific insights can be extracted. Radboud University We want to get the best out of science, others and ourselves. Why? Because this is what the world around us desperately needs. Leading research and education make an indispensable contribution to a healthy, free world with equal opportunities for all. This is what unites the more than 22,000 students and 5,000 employees at Radboud University. And this requires even more talent, collaboration and lifelong learning. You have a part to play! We offer: • Employment: 0.9 FTE. • A maximum gross monthly salary of € 4,402 based on a 38-hour working week (salary scale 10). • The exact salary depends on the candidate's qualifications and amount of relevant professional experience. • In addition to the salary: an 8% holiday allowance and an 8.3% end-of-year bonus. • Duration of the contract: 25 months. • The intended start date is 1 September 2021. • You will be able to use our Dual Career and Family Care Services. Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment and help your family settle in Nijmegen. • Have a look at our excellent employment conditions. They include a good work-life balance (among other things because of the excellent leave arrangements), opportunities for development and a great pension scheme. Apply directly Please use this link to apply: https://www.ru.nl/english/working-at/vacature/online-solliciteren/?tk=uk&re…. Address your application to Paul Tiesinga and submit it no later than 1 July 2021. Your application should include the following attachments: • Letter of motivation. • CV including contact details of two references. • Your research statement. The first round of interviews will take place on 6th July 2021. The second round of interviews will take place on 13th July 2021. For more information about this vacancy, please contact: Paul Tiesinga, Full Professor Tel.: +31 24 365 22 32 Email: p.tiesinga(a)science.ru.nl<mailto:p.tiesinga@science.ru.nl> Rembrandt Bakker, Postdoctoral Researcher Tel.: +31 24 365 26 33 Email: r.bakker(a)donders.ru.nl<mailto:r.bakker@donders.ru.nl> ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Dr. Astrid Lambrecht, Prof. Dr. Frauke Melchior ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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Postdoctoral position - Pinto Lab @ Northwestern University
by Lucas Pinto June 15, 2021

June 15, 2021

Dear colleagues, The Pinto Lab<http://www.pintolab.org> is seeking a postdoc who is excited about studying how neural circuits across many brain areas interact to support decision making, at the interface between experimental and computational neuroscience. In particular, the lab is interested in understanding the circuit mechanisms the control how these interactions are flexibly reconfigured when animals make decisions that use different underlying computations. To answer these questions, the candidate will use a combination high-throughput behavior in virtual reality, optical and genetic tools to measure and/or manipulate the dynamics of single neurons and neuronal populations, and computational approaches to understand both the behavior and its relationship to neural activity. We are a brand new lab that started in January 2021 at the Feinberg School of Medicine<https://www.feinberg.northwestern.edu/> at Northwestern University<http://www.northwestern.edu>, located in the heart of Chicago. Come join a vibrant neuroscience community<https://www.nuin.northwestern.edu/> in a world-class and highly livable city, working with a young PI committed to mentoring. Please visit our website<http://www.pintolab.org> for more details. Applicants should be nearing completion or already hold a PhD in neuroscience, biology, engineering, computer science, psychology or other related fields. Coding and/or experimental skills are preferred, but the applicant will have the opportunity to be trained in these techniques. We strongly encourage candidates from underrepresented groups to apply. Please send a CV, a one-page statement of research interests and skills, and contact information for 2-3 references to Lucas Pinto at lucas.pinto(a)northwestern.edu<mailto:lucas.pinto@northwestern.edu>. Best, Lucas - - - - - - - - - - - - - - - - - - - - - - - - - - - Lucas Pinto, M.D., Ph.D. Assistant Professor Department of Physiology Feinberg School of Medicine Northwestern University lucas.pinto(a)northwestern.edu<mailto:lucas.pinto@northwestern.edu> www.pintolab.org

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NEST Conference 2021 — Registration Deadline 21 June
by Hans Ekkehard Plesser June 15, 2021

June 15, 2021

Dear all, Just a little reminder that the registration deadline for the NEST Conference 2021 is on Monday next week, June 21. More information on the programme and how to register can be found on the conference website https://nest-simulator.org/conference This year's conference will again take place as a virtual conference on Monday/Tuesday 28/29 June 2021 followed by a virtual NEST User Hackathon until Friday 2 July. The NEST Conference provides an opportunity for the NEST Community to meet, exchange success stories, swap advice, learn about current developments in and around NEST spiking network simulation and its application. We are looking forward to seeing you all! Hans Ekkehard Plesser & many more -- Prof. Dr. Hans Ekkehard Plesser Head, Department of Data Science Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

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INCF/OCNS Software WG Dev session on SciUnit/NeuronUnit (June 21, 1600 UTC)
by Ankur Sinha June 14, 2021

June 14, 2021

Dear all, Apologies for the cross posts. The INCF/OCNS Software WG[1] is happy to announce the next Dev Session where members of the developer teams of commonly used neuroscience software introduce their software and then discuss their *development* pipelines. ---- In the next Dev Session, Rick Gerkin will introduce the SciUnit framework and discuss its development: https://ocns.github.io/SoftwareWG/2021/06/04/dev-session-rick-gerkin-sciuni… The session will be held at June 21, 2021, 1600 UTC over Zoom: https://ucl.zoom.us/j/91246735902?pwd=WVdVK3I5SGdlaDFZdllDQ0w2djVBdz09 Click here to see the event in your local time: https://www.timeanddate.com/worldclock/fixedtime.html?msg=Dev+session%3A+Ri… SciUnit is a discipline-agnostic framework for model validation, handling all of the testing workflow by using a implementation-independent interface to models. SciUnit also contains code for visualization of model results, and command line tools for incorporating testing into continuous integration workflows. SciUnit is used in model validation in neuroscience via NeuronUnit, which implements an interface to several simulators and model description languages, handles test calculations according to domain standards, and enables automated construction of tests based on data from several major public data repositories. ------- The aim of these sessions is to stimulate discussion of the development practices and tools used by different teams to improve the software we use while also improving our knowledge of these practices and tools. We also hope to encourage more users of these tools to contribute to their development to ensure their longevity. If you develop software for neuroscience, we would love to hear about your development pipeline. Please get in touch with the Software WG on our communication channels[2]. The WG is a community based group that is open to everyone at all levels of their careers (academic or otherwise). Please introduce yourself to the community on our channels to get involved. [1] https://ocns.github.io/SoftwareWG/ [2] https://ocns.github.io/SoftwareWG/pages/contact.html On behalf of the Software WG, -- Thanks, Regards, Ankur Sinha (He / Him / His) Research Fellow at the Silver Lab | http://silverlab.org/ Department of Neuroscience, Physiology, & Pharmacology University College London, London, UK Time zone: Europe/London

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Postdoc on Alzheimer's Disease modeling (Inria, UCL, BCAM)
by desroche June 14, 2021

June 14, 2021

Dear all, This is an invitation to join a multidisciplinary research on Alzheimer’s Disease (AD) for a 24-month postdoc. The project aims at combining mathematics and novel experiments to better understand the causes of the progressive symptoms of memory impairment in persons living with AD. Despite progress, AD research has hit a bottleneck and to date there are no effective treatments to prevent AD. It is now recognised that this is partially due to limitations in AD mice models that do not recapitulate human AD, to conflicting results and research focus on molecular mechanisms. We aim to overcome these limitations by exploring a gab in our understading of abnormal synaptic process (including neural-glia, inflammatory processes) and neural tissue dynamics that lead to AD. To this end, we will combine state-of-the-art experiments based on human brain tissue data, recent mice model that recapitulate human AD, mathematics and computations, which in tandem will address the multi-factorial nature of the disease for future successful drug development. The project is part of a long-standing collaboration between Mathieu Desroches (MathNeuro Project-Team, Inria Sophia Antipolis, France), Serafim Rodrigues (MCEN research group, Basque Center for Applied Mathematics, Bilbao, Spain) and Afia B Ali (School of Pharmacology, University College London, UK) on neurotransmission and its possible disruptions (see here <https://www.pnas.org/content/113/8/E1108.short>). The postdoc will strongly interact with these three researchers. Regarding profiles that we are seeking, familiarity of the candidate with mathematical modeling in Neuroscience. Experience with multiple-timescale systems is wishable but not mandatory. Ability and willingness to do programming, as well as analyse experimental data, will also be a strong point to select candidates. Please apply online via the following page: https://recrutement.inria.fr/public/classic/fr/offres/2021-03775 <https://recrutement.inria.fr/public/classic/fr/offres/2021-03775> For informal enquiries, please contact me: mathieu.desroches(a)inria.fr <mailto:mathieu.desroches@inria.fr> --------------------------------------------------------------------- Dr. Mathieu Desroches Research Scientist (Chargé de Recherche) MathNeuro Project Team Leader <https://team.inria.fr/mathneuro/> Inria Sophia Antipolis - Méditerranée, France http://www-sop.inria.fr/members/Mathieu.Desroches/ <http://www-sop.inria.fr/members/Mathieu.Desroches/>

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CFP Workshop on Spatio-temporal Aspects of Embodied Predictive Processing @ ICDL2021
by Stefan Heinrich June 14, 2021

June 14, 2021

Call For Contributions - Workshop on Spatio-temporal Aspects of Embodied Predictive Processing @ IEEE ICDL2021 Aims and Scope: Understanding human intelligence and building strong AI systems is a key challenge for our generation. A particularly puzzling aspect is that the human brain seems to cope very well with the highly variable and uncertain nature of perception and action, regarding both their signal characteristic and how they extend over time. Furthermore, it seems apparent that the information processing in the brain always involves previous bodily experiences and all our senses, thus is embodied and crossmodal. For explaining these characteristics, there are strong accounts that the brain is constantly predicting sensory input and feedback while minimising free energy in the prediction and is hierarchically abstracting the perception as well as hierarchically composing action. Furthermore, it is also hypothesised that mechanistic priors in the brain’s information processing induce a failure of hierarchical inference in the brain, accounting for atypical perception and action of psychiatric disorders. For example, some brains might have developed to focus too strongly on current sensory input while others might focus too strongly on memorised previous experience. A typically developed brain, in contrast, would show a fine balance compared to these two extreme priors. The big open mystery is: how is the brain developing this on a mechanistic level and thus how can this get learned within an AI system? Thus, to lift this mystery, we further need to bring together research from computational neuroscience, cognitive psychology, and artificial intelligence. With this workshop, we particularly want to wrap up different recent hypotheses, models, and experiments and discuss in-depth how to shape future imaging, behavioural, and developmental robotics studies as a complement to computational modelling and bio-inspired artificial intelligent algorithms. As a guiding theme, we aim to approach the following central questions: - How does the brain learn spatio-temporal stochasticity in perception and action? - What is the role of priors in learning spatio-temporal adaptive prediction? - How can developmental robotics help us to study spatio-temporal stochasticity as an analogy to infant learning? We examine these questions with the insight from invited key speakers from complementary fields as well as original contributions in breakout sessions in order to conclude the next steps within in a panel discussion. All information online: https://sites.google.com/view/stepp21/home Keynotes/Panellists: - Jun Tani, Cognitive Neurorobotics, Okinawa Institute of Science and Technology (OIST) - Marcel van Gerven, Artificial Cognitive Systems, Donders Institute, Radboud University - Takuya Isomura, Brain Intelligence Theory, RIKEN Center for Brain Science - Takamitsu Watanabe, Brain Network Dynamics, International Research Center for Neurointelligence (IRCN), The University of Tokyo Contributions: We invite submissions of extended abstracts on ongoing research that focuses on one or several of our guiding questions as contributions. In addition to the live presentation and discussion during the workshop, the contributions will be made public in workshop proceedings. - Extended abstract submission deadline: 11.07.2021 - Decision & Notification: 25.07.2021 - Camera-ready version due: 08.08.2021 - Workshop online: 22.08.2021 Submission website: https://sites.google.com/view/stepp21/ => Contribute Organisers: Stefan Heinrich, IRCN, The University of Tokyo, Japan Shingo Murata, Dept. Electronics and Electrical Engineering, Keio University, Japan Yukie Nagai, IRCN & Institute for AI and Beyond, The University of Tokyo, Japan Yuichi Yamashita, National Center of Neurology and Psychiatry, Japan -- ************************************************************* Dr. Stefan Heinrich Postdoctoral Project Researcher Cognitive Developmental Robotics Lab The University of Tokyo, Institutes for Advanced Studies, International Research Center for Neurointelligence Email: heinrich.stefan(a)ircn.jp https://developmental-robotics.jp/en/members/stefan_heinrich/ https://ircn.jp/en/ https://stefanheinrich.net/ *************************************************************

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Multiple postdoctoral openings in reinforcement learning in multi-scale brain networks at Washington University in St. Louis
by Ching, ShiNung June 14, 2021

June 14, 2021

Multiple postdoctoral openings in modeling reinforcement learning in multi-scale brain networks at Washington University in St. Louis Multiple postdoctoral openings are available for a new and large, multi-PI project to study the circuit underpinnings of reinforcement learning and decision-making. A key focus is on understanding multiple time-scales of information processing in neural circuits and involvement of neuron-astrocyte interactions. Experiment- and theory-forward positions are available. Applicants should have prior experience in neuroscience (computational or otherwise), modeling of large-scale systems, optimization, machine learning or related areas. Positions will be cross-appointed between Engineering and Neuroscience. Washington University in St. Louis is an independent, Research 1 university in St. Louis, MO, USA, with nearly 60 of the university's graduate and undergraduate programs ranked in the top 25 by US News & World Report. www.wustl.edu Interested applicants are invited to send a CV and brief description of interests to ShiNung Ching: shinung(a)wustl.edu

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EITN Seminar: Paul Miller (Brandeis U, Waltham MA, USA) - Friday 18 June 16:00
by Zélie Tournoud June 14, 2021

June 14, 2021

Dear colleagues, We are pleased to welcome *Paul Miller* from Brandeis University (Waltham MA, USA) for an online seminar this week. It will take place on Zoom on *Friday 18 June at 16:00* CEST (Paris time). *Title**: **Information processing in neural circuits with multiple quasi-stable attractor states* *Abstract: *Circuits containing clusters of neurons with strong within-cluster excitatory connections and random between-cluster connections can possess multiple activity states, with each state defined by the set of clusters with stably high versus low neural firing rates. Noise or adaptive processes can render the states quasi-stable such that in the presence of constant input, or following successive identical inputs, the network can progress through a sequence of different activity states. Here we study the properties of such models, including the role of finite size effects in producing multistability in networks with Gaussian random cross-coupling, and we assess the extent to which such state sequences might subserve information processing and behavior in a range of cognitive tasks. Join on the day on the event at: > Topic: EITN seminar: Paul Miller (Brandeis University) > Time: 18 June 2021 04:00 PM Paris (CEST) > Join Zoom meeting: > https://zoom.us/j/99754103845?pwd=UGlHSjgySTBXeUtvSW5SVUVMRnFiZz09 > <https://zoom.us/j/99754103845?pwd=UGlHSjgySTBXeUtvSW5SVUVMRnFiZz09> > Meeting ID: 997 5410 3845 > Password: 634477 We look forwards to see you at the seminar. Kind regards, The EITN Team

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Adaptive Machines: Leveraging Neuroscience for Lifelong Learning Systems
by Andrea Soltoggio June 14, 2021

June 14, 2021

Dear Connectionists, I’d like to bring your attention to the Research Topic “Adaptive Machines: Leveraging Neuroscience for Lifelong Learning Systems” to be co-hosted by Frontiers in Neuroscience, Robotics and AI, Big Data, Artificial Intelligence, Neurorobotics and Computational Neuroscience. The article submission deadline is the 30th of September. Link: https://www.frontiersin.org/research-topics/20053/adaptive-machines-leverag… Description: Artificial intelligence has always sought inspiration in the brain. Artificial neural networks (ANNs), in particular, were modeled after their biological counterparts (biological neural networks, BNNs). However, state-of-the-art deep networks are drastically different from BNNs. Their architectures (at both the single-neuron and macro levels), learning algorithms, and failure conditions share little in common with brain circuit dynamics. In particular, state-of-the-art deep learning is optimized for single, well-defined, static tasks. Deep networks struggle to learn multiple or evolving tasks over time (i.e., continual learning) or to adjust their processing based on environmental conditions. They are also less modular than BNNs, and thus less energy efficient, and utilize little-to-no feedback signals. We believe that deep networks suffer from these limitations because their modeling of brain dynamics is too superficial. Modeling more sophisticated neural mechanisms is therefore key for deep networks to achieve continual or lifelong learning and to cope with open-ended, dynamic environments. The goal of this Research Topic is to publish novel models and/or algorithms that expand the capabilities of deep learning (e.g., achieve better continual learning) by incorporating additional properties of BNNs. We are also interested in neuroscience research that elucidates mechanisms that can be leveraged by the AI community. Neuroscience has uncovered a wide range of learning and regulatory mechanisms, at scales ranging from single molecules to the entire nervous system, that help the brain learn, remember, and adapt. These include replay (systems-level consolidation), neuromodulation, neurogenesis, neuroevolution, attention, homeostatic plasticity, and synaptic consolidation. There exist some deep learning techniques motivated by these mechanisms (e.g., experience replay or attention networks), but they have rarely been used for lifelong learning. As such, our focus will be on approaches that leverage brain-like principles---ideally biologically well-grounded---to solve problems currently beyond the capabilities of the state of the art. We will also welcome neuroscience research that helps to elucidate the brain’s mechanisms, in the hope that they can be used by the next generation of machine learning models. The scope of this Research Topic covers: (1) biologically inspired techniques in deep learning (2) neuroscience research on how the brain facilitates learning and adapts to different contexts We seek to address continual or lifelong learning, transfer learning, and other ML scenarios that go beyond the traditional, train-then-test learning paradigm. Since machine learning is an experimental field, a paper must include experimental results to be accepted; however, we encourage authors to include theoretical analyses of their methods. We aim to collect the following types of manuscripts: Original Research and Brief Research Reports. Since the goal of this Research Topic is to publish highly novel, experimentally grounded work, we are not interested in Reviews (Systematic, Policy and Practice, etc.), General Commentaries, or Opinions. In addition, since the editorial board does not include medical experts, we cannot accept Clinical Trials or Study Protocols. The Research Topic will be edited by Rolando Jose Estrada, Georgia State University, USA Andrea Soltoggio, Loughborough University, UK Praveen K. Pilly, HRL Laboratories, USA Vincenzo Lomonaco, University of Pisa, Italy, Davide Maltoni, University of Bologna, Italy. Please consider submitting your original research to this Research Topic. Do not hesitate to get in touch if you wish to discuss your contribution. Best wishes, Andrea -- Dr. Andrea Soltoggio (he/him or they/them) Senior Lecturer (Associate Professor) in Artificial Intelligence Department of Computer Science, School of Science & Intelligent Automation Centre https://www.intelligent-automation.org.uk/about-us/centre-staff & Centre for Information Management https://www.lboro.ac.uk/departments/sbe/cim/ Haslegrave Building, N.2.03 Loughborough University LE11 3TU, UK Email: a.soltoggio(a)lboro.ac.uk<mailto:a.soltoggio@lboro.ac.uk> Web: http://www.lboro.ac.uk/departments/compsci/staff/dr-andrea-soltoggio.html

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be a mentor for Neuromatch Academy!
by Marius Pachitariu June 11, 2021

June 11, 2021

Participate as MENTOR in Neuromatch Academy Neuromatch Academy returns this year with twice as many students and TAs participating in twice as many courses. If you are faculty or postdoc with some experience, please sign up to be a mentor for the Computational Neuroscience (syllabus <https://github.com/NeuromatchAcademy/course-content>) and/or the Deep Learning course (syllabus <https://github.com/NeuromatchAcademy/course-content-dl>). NMA is unique in reaching enthusiastic students from all over the world, most of whom cannot afford a traditional summer school. NMA 2020 reached students from ~70(!) countries. This year we have students from >100 !!! Mentors provide guidance and feedback on 3-week long projects that students complete in groups of 4-6. You will be algorithmically matched with students that have similar research interests to you.The mentorship happens in 4-5 sessions of 30-60 minutes each, leading to a time commitment of up to 5 hours per group. Mentors can take on 1-4 groups. Beginner groups are encouraged to use project templates, such as the ones here (link <https://docs.google.com/presentation/d/1v7fuzi9Y9RV12CysMBi5rxZKhjnWD5Js29U…>). Please consider contributing a project template, by simply adding a slide to the public google doc. Mentoring is relatively easy because you don’t need to prepare anything. Nonetheless, your feedback is extremely valuable to the students, who are taking their first steps in neuroscience / deep learning. We also encourage you to provide career advice, and optionally set up meetings with TAs after the summer school. Our collective effort to teach and mentor these young scientists and engineers pays off in the long-term: their positive experience at NMA inspires them to consider careers in our research fields. The application for mentors can be found below. Course starts July 5th, so please apply soon! https://portal.neuromatchacademy.org/

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Senior Postdoc ("Akademischer Rat") in the Reichenbach lab, Friedrich-Alexander-University (FAU) Erlangen-Nuremberg, Germany
by Reichenbach, Tobias June 11, 2021

June 11, 2021

The newly founded Chair for Sensory Neuroengineering at the new Department Artificial Intelligence in Biomedical Engineering is looking for a Senior Postdoc ("Akademischer Rat"). In close collaboration with clinical and industrial partners, the Chair researches on the neural foundations of hearing, as well as on new technology for better treatments of hearing impairment. Reseach topics are, for instance, the development and application of AI methods to analyse neurological data on human speech processing as well as the development of AI methods to construct audiovisual speech signals for better speech comprehension. The Senior Postdoc should shape this research field with their own innovative projects. The appointment will initially be for three years, and can be made permanent upon excellent performance. To apply, please send a letter detailing your motivation, a CV, copies of your degrees and details of three referees. Please combine all documents into a single pdf and send them per email with subject “Application Senior Postdoc” to Prof. Dr. Tobias Reichenbach (tobias.j.reichenbach(at)fau.de<http://fau.de>). FAU is the most innovative university in Germany and ranks second among the most innovative European universities. It is located in one of the most attractive regions in Germany. Erlangen is a bicycle-friendly city with 100,000 inhabitants, former home of the Huguenots as well as a key location for Siemens. It is close to Nuremberg, a city with a population of half a million and a metropolitan flair. The mixture of academia, innovative companies, art and culture makes the region the perfect place for creative minds, keen athletes and nature lovers. More information is available here: https://www.jobs.fau.de/jobs/senior-postdoc-in-computational-neurotechnolog… ------------------------------------------- Prof. Dr. Tobias Reichenbach Department Artificial Intelligence in Biomedical Engineering (AIBE) Friedrich-Alexander-University (FAU) Erlangen-Nuremberg Henkestrasse 91 91056 Erlangen https://reichenbach.bg-research.cc.ic.ac.uk/index.html

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Information theory workshop at CNS*2021 -- call for contributed talks
by Joseph Lizier June 10, 2021

June 10, 2021

Dear all, We are pleased to announce that the Workshop on Methods of Information Theory in Computational Neuroscience<https://abzinger.github.io/202107-CNS2021-ITW.html> will be held once again at the CNS*2021<http://www.cnsorg.org/cns-2021> conference, online. The workshop will be held during sessions over two days of the main conference, July 6 and 7 (time TBA). Our confirmed speakers so far include the following (schedule available soon): * Tatyana Sharpee, Salk Institute * Raul Vicente, University of Tartu * Viola Priesemann, Max Planck Institute for Dynamics and Self-Organization * Fernando Rosas, Imperial College London * Fleur Zeldenrust, Radboud University * Aaron Gutcknecht, University of Goettingen * Lucas Rudelt, Max Planck Institute for Dynamics and Self-Organization * ... more TBA! Also, we would like to call for contributions of talks. If you are interested in contributing a talk, please send a title and abstract to Abdullah Makkeh (abdullah.alimakkeh(a)uni-goettingen.de<mailto:abdullah.alimakkeh@uni-goettingen.de>) at your earliest convenience (earlier submissions will be prioritised). Please pay attention to the registration<https://www.cnsorg.org/cns-2021-registration-fees> for CNS*2021 (early bird deadline and fees), and see our website<https://abzinger.github.io/202107-CNS2021-ITW.html> for more details. We hope you will join us there! Organising Committee: Michael Wibral (co-chair) Abdullah Makkeh (co-chair) Joseph Lizier

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TEX2021 - Bringing together Predictive Processes and Statistical Learning
by Yamil Vidal June 8, 2021

June 8, 2021

You are all invited to: TEX2021 - Bringing together Predictive Processes and Statistical Learning A free online symposium organized by Yamil Vidal and Davide Crepaldi. Description: While the research communities studying Predictive Processes and Statistical Learning sprout from different traditions, they share a core interest in how our brains pick up on patterns in the environment. In this two-days symposium we will bring these communities closer by sharing talks by some of the leading researchers of these fields. When: 1st and 2nd of July Speakers: - Tristan Bekinschtein (Consciousness and Cognition Lab, Department of Psychology, University of Cambridge) - Lucia Melloni (Department of Neuroscience, Max Planck Institute for Empirical Aesthetics. Department of neurology, NYU Grossman School of Medicine) - Padraic Monaghan (Department of Psychology, Lancaster University) - Maria Chait (Ear Institute, University College London) - Floris de Lange (Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen) - Caspar Schwiedrzik (Neural Circuits and Cognition Lab, European Neuroscience Institute Goettingen. Perception and Plasticity Group, German Primate Center - Leibniz Institute for Primate Research) - Lori Holt (Department of Psychology, Carnegie Mellon University) - Nicola Molinaro (BCBL, Basque Center on Cognition, Brain and Language) Schedule and more info at the registration form: https://sissa-it.zoom.us/webinar/register/WN_nBOv5NWZQ36HSH7nyffazg And here is the announcement that we made through Twitter: https://twitter.com/CrepaldiLab/status/1400856625896902656 We would be very happy to count you among the attendees. Please spread the word. Best regards, Yamil and Davide Dr. Yamil Vidal Cognitive Neuroscience Sector Scuola Internazionale Superiore di Studi Avanzati - SISSA via Bonomea, 265 34136 Trieste, ITALY

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EITN Fall School in Computational Neuroscience : Applications open!
by Zélie Tournoud June 8, 2021

June 8, 2021

Dear colleagues, We are happy to let you know that applications for the *EITN Fall School in Computational Neuroscience* are currently open, until the 2nd of July 2021. This *10-days intensive course in computational neuroscience* will take place in *P**aris, France from 15 to 24 September 2021*. This is a yearly event, although previous occurrences took place in the spring. We choose to keep it relatively small-scale in order to facilitate interactions between participants and teaching staff, there are about 20 seats available. There will, therefore, be a selection made after applications are closed. We encourage you to share the word widely with your collaborators and networks so that everyone who might be interested can get the chance to apply. Applications need to be addressed by email with a *resume (CV)* and a *cover letter* at *eitn(a)neuro-psi.fr*. Please make sure to use an explicit email title such as "Application to EITN Fall School". *Why join?* * 10 days of intensive training in computational neuroscience provided by researchers from all over Europe * Small scale event: get to connect! * A complete program: o Cellular models, and models of brain signals Circuit models and networks o Mean-field models o Whole-brain models * Hands-on learning schedule based on: o Morning classes and tutorials o Group projects in the afternoon o Free time in the evenings to visit Paris *Selection criteria:* 1. Work or study in neuroscience or related 2. Experience in python programming would help 3. Priority to PhD students, although Master students and post-docs are welcome to apply *Practical information:* * Subscription fee 400€. * If selected, you will need to bring your own laptop with a few pre-installed programs. * The tuition fee includes lunch, coffee, access to conference facilities and internet connection during the 10 days of the course. You can also consult these information online <https://www.eitn.org/index.php/calendar-event/eventdetail/737/-/eitn-fall-s…> or by downloading the PDF flyer: https://www.eitn.org/images/events/EITN-FallSchool-2021_Flyer.pdf Thank you very much for applying or sharing with your relevant contacts. Kind regards, The EITN Team

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Postdoc Position at Cardiff University Brain Research Imaging Centre
by Jiaxiang ZHANG June 8, 2021

June 8, 2021

[Apologize for cross-posting] Dear all, We are seeking an enthusiastic early-career scientist for a research associate position at Cardiff University Brain Research Imaging Centre (CUBRIC). The successful candidate will join a collaborative and multidisciplinary research team to work on the neurocognitive mechanisms of human decision-making, integrating multimodal brain imaging (MEG, functional MRI and diffusion MRI) and computational modelling. The post holder will develop computational models that describe data from behavioural and brain imaging experiments, in particular to take a lead role in integrating large-scale computational simulations with imaging results from multiple modalities. The research aims to understand the computational and neurocognitive processes of human decision-making, and how decision deficits may arise due to brain injury or neurodegeneration. The research associate will also be expected to collaborate with other researchers in the team on imaging data analyses and data curation. You will have access to imaging facilities at CUBRIC and several multimodal imaging datasets. Cardiff University Brain Research Imaging Centre (CUBRIC) houses a unique combination of state-of-the-art facilities and world-leading expertise, with 4 human MRI systems (2 x Siemens Prisma, 1 x Siemens Connectom, 1 x Siemens 7T), MEG, EEG, TMS, tDCS, clinical research units and testing labs. Further details of CUBRIC can be found on our webpage (http://sites.cardiff.ac.uk/cubric) This is a full-time, fixed-term position until February 2023, available to start now. Remote working is possible if COVID-19 restrictions are in place. For informal enquiries, please contact Dr Jiaxiang Zhang ( zhangj73(a)cardiff.ac.uk) A formal application needs to be submitted via the link online ( https://www.jobs.ac.uk/job/CEQ831/research-associate) *Application deadline: June 13th, 2021.* *Essential Criteria* 1. A PhD degree in a relevant discipline (e.g., mathematics, computer science, engineering, physics or psychology) 2. Research experience or a strong interest in human decision-making 3. Strong experience in computational models of cognitive processes and/or macroscopic neural systems, including the use of neural mass models or neural field models 4. Experience of analysing brain imaging data in one or more modalities (e.g., diffusion MRI, BOLD functional MRI, MEG/EEG), using common software packages 5. Strong programming skills (e.g., Matlab, Python, C/C++ or R) 6. Experience with Unix/Linux environment for data analysis, including bash scripting and parallel computing on high-performance clusters 7. Proven ability to publish high-quality research in peer-reviewed academic journals 8. Knowledge of software development cycles and best programming practices, including coding standards, version control administration, debug and code sharing, with strong commitments to open science practices 9. Excellent written and verbal communication skills, evidenced by publications and/or conference presentations 10. Strong interpersonal skills, including proven ability to work cooperatively within a team while also being able to take the initiative *Desirable Criteria * 1. Experience of brain functional and structural connectivity analyses 2. Experience in statistical methods (e.g., GLM, mixed models, multivariate statistics, hierarchical models and Bayesian statistics) and/or machine learning methods 3. Experience in deep learning models of imaging processing --- Dr. Jiaxiang Zhang Cardiff University Brain Research Imaging Centre (CUBRIC) School of Psychology Cardiff University Maindy Road, Cardiff, CF24 4HQ https://ccbrain.org

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[jobs] One-year Postdoc on “Sparse coding for bio-inspired vision models” at CentraleSupèlec, Gif-sur-Yvette, France
by PERRINET Laurent June 7, 2021

June 7, 2021

Dear Colleagues, Applications are invited for a one-year Postdoc position, starting in September 2021 or as soon as possible thereafter, to work under the joint supervision of Dario Prandi<https://dprn.github.io/> (CNRS, Université Paris-Saclay), Luca Calatroni<https://sites.google.com/view/lucacalatroni/home> (CNRS, Université Côte d'Azur), and Laurent Perrinet<https://laurentperrinet.github.io/> (CNRS, Institut de Neurosciences de la Timone). The position is financed by the ANR Rubin-Vase (https://anr.fr/Projet-ANR-20-CE48-0003) and the research focus will be on linking the bio-inspired models studied by D. Prandi and L. Calatroni (see e.g. [1]) to the sparsity promoting neural architectures investigated by L. Perrinet (see, e.g., [2]). The successful applicant will have a strong applied mathematical background, ideally in the fields of sparse optimization and/or dynamical systems, and a good familiarity with neural architectures and the associated implementation issues. Strong skills in coding and programming using standard optimization/deep learning languages (e.g., Python, PyTorch, Julia, MATLAB…) are required. The gross salary is of 50k-59k euros (depending on the seniority of the applicant), and the position comes with no teaching duties. Although the position is officially based at CentraleSupèlec (Université Paris-Saclay), the successful applicant is expected to spend fairly long periods at the INT in Marseille and I3S in Sophia-Antipolis, to work with the co-supervisors. Candidates are asked to write directly to Dario Prandi (dario.prandi(a)centralesupelec.fr<mailto:dario.prandi@centralesupelec.fr>), attaching a CV, a short description of current research interests, and names and contact addresses of at least two reference contacts (no formal letters of recommendation are required). Applications are reviewed continuously, until positions are filled, with a first evaluation round starting on the 14th of June, 2021. Thanks for distributing this announcement to potential candidates! References [1] Bertalmío, M., Calatroni, L., Franceschi, V. et al. Cortical-Inspired Wilson–Cowan-Type Equations for Orientation-Dependent Contrast Perception Modelling. J Math Imaging Vis 63, 263–281 (2021). https://arxiv.org/abs/1910.06808 [2] Boutin V, Franciosini A, Chavane F, Ruffier F, Perrinet L (2021) Sparse deep predictive coding captures contour integration capabilities of the early visual system.<https://laurentperrinet.github.io/publication/boutin-franciosini-chavane-ru…> PLoS Comput Biol 17(1): e1008629. https://doi.org/10.1371/journal.pcbi.1008629 -- Laurent Perrinet - INT (UMR 7289)/CNRS https://laurentperrinet.github.io/

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[news] Call for Participation - The Chef's Hat Cup @ IJCAI2021
by Pablo Vinicius Alves De Barros June 3, 2021

June 3, 2021

Deadline Extended! - The Chef's Hat Cup @ IJCAI2021 I. Aim and Scope Most of the current Reinforcement-Learning solutions, although having real-world-inspired scenarios, focus on a direct space-action-reward mapping between the agent's actions and the environment’s state. That translates to agents that can adapt to dynamic scenarios, but, when applied to competitive and/or cooperative cases, fail to assess and deal with the impact of their opponents. In most cases, when these agents choose an action, they do not take into consideration how other agents can affect the state of the scenario. In competitive scenarios, the agents have to learn decisions that a) maximize their chances of winning the game, and b) minimize their adversaries' goals, while in cooperative scenarios b) is inverted. Besides dealing with complex scenarios, such solutions would have to deal with the dynamics between the agents themselves. In this regard, social reinforcement learning is still behind the mainstream applications and demonstrations of the last years. We introduce here the Chef's Hat Cup, a competition that aims at the development of the most challenging artificial players! The competition is separated into two tracks: a competitive and a cooperative scenario. In the first track, the participants will use the already available simulation environment to develop the most effective agents to play the Chef’s Hat card game and be the winner. In the second track, they will have to develop an agent that can increase the chances of a dummy agent winning the game. More information: https://www.whisperproject.eu/chefshat#competition II. Deadlines Starting Date: April 20, 2021 Final submission: July 15, 2021 Winners Announcement: July 29, 2021 III. Team Registration Teams of up to five persons are invited to participate in the competition. You can register by sending the following information: Team name Participant Names and affiliation to this email: pablo.alvesdebarros(a)iit.it IV. Prizes The prizes will be sponsored by the Contact Unit at the Italian Institute of Technology, and will be organized as follows: Competitive Track - Winner – 300 EUR - Second – 150 EUR - Third – 50 EUR Cooperative Track - Winner – 300 EUR - Second – 150 EUR - Third – 50 EUR V. Organizers Pablo Barros, Italian Institute of Technology (IIT), Italy Leandro Honorato, University of Pernambuco, Brazil Marco Matarese, Italian Institute of Technology (IIT), Italy Alessandra Sciutti, Italian Institute of Technology (IIT), Italy ---------------------------------------- Dr. Pablo Barros Postdoctoral Researcher - CONTACT Unit Istituto Italiano di Tecnologia – Center for Human Technologies Via Enrico Melen 83, Building B 16152 Genova, Italy email: pablo.alvesdebarros(a)iit.it website: https://www.pablobarros.net<http://www.pablobarros.net><https://www.p> twitter: @PBarros_br

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PostDoc in Machine Hearing
by Sarah Verhulst June 2, 2021

June 2, 2021

Dear list, We have a 3-yr post-doc vacancy in my Hearing Technology lab in Ghent, Belgium. We do research on the interface between computational neuroscience and audio signal processing to develop human-inspired machine-hearing applications. More info on the position and application info can be found here (closing date 5th of July): https://tinyurl.com/4h9m497b Feel welcome to distribute, With best regards, Sarah —— Sarah Verhulst Associate Professor Hearing Technology @ WAVES Department of Information Technology Technologiepark 126, 9052 Zwijnaarde T +32 9 331 48 44 T admin +32 09 264 33 21 www.waves.intec.ugent.be/hearing-technology<http://www.waves.intec.ugent.be/hearing-technology> www.gasp.ugent.be<http://www.gasp.ugent.be> @HearingTechLab @GentAuditorySci GitHub: HearingTechnology

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