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Registration open for ENCODS 2023
by Delamare, Geoffroy 17 Feb '23

17 Feb '23

Dear fellow students, This year the ENCODS conference will take place again! ENCODS 2023 Faro, Portugal, on 01-02 May 2023! The European Neuroscience Conference by Doctoral Students (ENCODS) is organised by PhD students for PhD students. During the two days you have the opportunity to present your current work in the form of a poster or talk to an international audience. This year's theme is "Labcoats and Laptops: Neuroscience through different lenses", and we're aiming to bring together different disciplines of neuroscience and how we can all work together. In which area of neuroscience do you work? We are sure that your work is a great match for our topic and will contribute to an exciting and interesting dialogue. Here are the important facts: The registration fee is 100 € for FENS members and students at the University of Algarve and 120 € for non-FENS members. Food is provided, we have organised a catering service for you. We are also happy to help you find suitable accommodation and organise a bus transport from the city centre to the venue. University of Algarve: Gambelas Campus Faro, Portugal Registration ends on the 3rd of March!! Register here: https://www.fens.org/news-activities/fens-and-societies-calendar/training-e… https://www.fens.org/careers/networks/encods 17th of March 2023: Arrival of the acceptance letters 31st of March 2023: Deadline to pay the registration fees Follow us across our social media platforms using this link: https://linktr.ee/encods2023 We are very much looking forward to seeing you at ENCODS!!! Your ENCODS 2023 Organizing Committee

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2 PhD positions in Computational Neuroscience at INRIA, Lyon, France, starting on September 2023
by Hugues Berry 16 Feb '23

16 Feb '23

Dear all, 2 PhD positions in computational neuroscience are available in the AIstroSight team, INRIA, Lyon, France (https://team.inria.fr/aistrosight/) starting on September 2023. Our interdisciplinary team aims at developing innovative numerical methods for the search of new drug candidates to treat brain diseases, targeting neurons as well as glial cells. We value diversity, trust, growth, equity and creativity. - Project 1: Modeling compartmentalized second messenger networks in the retinal growth cones. This project is part of an ANR grant, in collaboration with Xavier Nicol's lab in Paris: http://xaviernicol.toile-libre.org/ - Project 2: Modeling the neurovascular unit. This project will consist in developing a mechanistic model of astrocytic endfeet in the context of neurovascular coupling. The project will be carried out in strong collaboration with neuroscientists working on endfeet. The students will be co-supervised by Dr. Audrey Denizot (https://adenizot.github.io/) and Dr. Hugues Berry (https://www.inrialpes.fr/Berry/) We are looking for students who have some experience in programming/mathematical modeling and previous expertise or interest in cell biology/neuroscience. The students must be fluent in English, both speaking and writing. No knowledge of French is required. Most importantly, we are looking for future colleagues who are eager to learn and grow, and who are driven by scientific curiosity. Please reach out to audrey.denizot(a)inria.fr or hugues.berry(a)inria.fr with a one-page statement presenting your interests and goals as well as a CV. Best regards, Hugues BERRY ------------------------ Deputy scientific director of Inria for digital health and biology — Project-Team AIstroSight -- https://team.inria.fr/aistrosight Inria-Université Claude Bernard Lyon 1 Hospices Civils de Lyon-Theranexus Inria Lyon research center Batiment CEI-2 56 Blvd Niels Bohr CS 52132 69603 Villeurbanne cedex France Tel. (Office): +33 (0)4 72 43 75 01 Tel. (Mobile): + 33 (0)6 70 77 63 39 www.inrialpes.fr/Berry

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Funded PhD Scholarship in Developmental Neurorobotics at Sheffield Hallam University (UK)
by Di Nuovo, Alessandro 16 Feb '23

16 Feb '23

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

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Generative Episodic Memory conference - deadline for abstracts
by Vinita Samarasinghe 16 Feb '23

16 Feb '23

The deadline to submit abstracts for GEM 2023 - Generative Episodic Memory: Interdisciplinary perspectives from neuroscience, psychology and philosophy - is fast approaching. The DFG-funded research consortium “FOR 2812 – Constructing scenarios of the past” https://for2812.rub.de is proud to announce a call for abstracts for its biennial conference *GEM 2023* (Generative Episodic Memory: Interdisciplinary perspectives from neuroscience, psychology and philosophy), which will be held *in person*at the Ruhr University Bochum, Germany from 12^th to 14^th June 2023. For more information on the conference please visit https://for2812.rub.de/gem2023. *Keynote speakers: * * Ali Boyle (LSE) * Felipe De Brigard (Duke U.) * Christian Leibold (U. Freiburg) * Kenneth Norman (Princeton U.) * Peggy St. Jacques (U. Alberta) * Maria Wimber (U. Glasgow) We invite submissions for symposia, talks and posters. *Please note that all presentations are in person.* *Funding for early career researchers is available *(visit https://for2812.rub.de/gem2023/early_career_researcher_program for more details). Episodic memories are widely regarded as memories of personally experienced events. Early concepts about episodic memory were based on the storage model, according to which experiential content is preserved in memory and later retrieved. However, overwhelming empirical evidence suggests that the content of episodic memory is – at least to a certain degree – constructed in the act of remembering. Even though very few contemporary researchers would oppose this view of episodic memory as a generative process, it has not become the standard paradigm of empirical memory research. This is particularly true for studies of the neural correlates of episodic memory. Further hindering progress are large conceptual differences regarding episodic memory across different fields, such as neuroscience, philosophy, and psychology. This interdisciplinary conference therefore aims to bring together researchers from all relevant fields to advance the state of the art in the research on generative episodic memory. *Abstract* submission deadlines [GMT +1 (CET)]: Abstract submission – 15.03.2023 Notification of acceptance – 15.04.2023 Submission guidelines: Abstracts mustbe submitted in English and be no longer than 500 words.Submitted work must be original and unpublished andsubmitted electronically athttps://www.conftool.net/gem2023/. Types of submissions: * Talks * Symposia: In addition to submitting individual talks there is also the option to submit a set of talks (henceforth called symposium). Symposiamust be interdisciplinary in nature, i.e., they must contain talks from at least two of the following disciplines: computational neuroscience, philosophy, psychology, neuroscience, and must comprise 3 talks. Please note that if one or more of the talks that make up the symposium are rejected the remainingtalks are not automatically rejected. They will be scheduled into the general program by the program committee. * Posters Please ensure that your files are in PDF format and are no larger than 10 MB. We look forward to welcoming you in Bochum. Vinita Samarasinghe Coordinator -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/73 Postfachnummer 110 Universitätstr. 150 44801 Bochum Tel: +49 (0) 234 32 27996 Email:samarasinghe@ini.rub.de

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Neuroscience PhD position at Newcastle, UK
by Andrej Bicanski 15 Feb '23

15 Feb '23

Dear Colleagues, Please circulate this to any students that may be interested in a neuroscience PhD project based in Newcastle University (UK), co-supervised by Dr. Quoc Vuong and myself. The Topic: We will explore the cross-domain function of the medial temporal lobe with fully immersive virtual reality and with eye-tracking, using new behavioural paradigms and fMRI. We may also incorporate some modelling. Funding: Funded for 3 years and international students are welcome to apply. Deadline: 2nd of March Link with more information: https://www.findaphd.com/phds/project/exploring-the-cross-domain-function-o… 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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Special Issue: Machine Learning in Neuroimaging for Psychiatry
by Rogene Eichler West 13 Feb '23

13 Feb '23

Dear Colleagues, The journal Clinical EEG and Neuroscience is soliciting papers for a special issue on Machine Learning in Neuroimaging for Psychiatry. We especially encourage papers on the development or selection of medications for the treatment of mental health issues. Preference will be given to submissions where the authors include clinicians, rather than a team comprised entirely of data scientists. https://us.sagepub.com/en-us/nam/journal/clinical-eeg-and-neuroscience May1 First draft due July 1 Reviews done. Each invited author reviews 2 other invited submissions as this will be a collegial process. Oct 1 Revisions due The curation will be through guest editors of this issue [Martijn Arns, Sebastian Olbrich, and myself] rather than through the journal’s normal submission portal. Please contact me with any questions or potential submission ideas. We look forward to hearing from you. ____________________________________________ Rogene M. Eichler West, PhD, QEEGD Diplomate in Quantitative Electroencephalography Northwest Neuro Professionals, LLC Associate Editor, Sage Publishing Clinical EEG and Neuroscience Senior Research Scientist in Cognitive and Behavioral Modeling Pacific Northwest National Laboratory

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Call for paper: Biological and Digital Markers in Sleep, Circadian Rhythm, and Epilepsy using Artificial Intelligence
by Sun Haoqi 13 Feb '23

13 Feb '23

Dear Comp-neuro mailing list members, We invite you to submit your work to Frontiers in Physiology: Biological and Digital Markers in Sleep, Circadian Rhythm, and Epilepsy using Artificial Intelligence. YES - I would like to participate: Click here to Confirm participation Frontiers average article review time: 61 days from submission to final decision NO - I am unable to participate in this project: Click here to decline participation Deadline: Manuscript Submission: July 9th, 2023 Kind Regards, Haoqi Sun Topic Editor, Computational Physiology and Medicine Section, Frontiers in Physiology

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PhD position in Computational Modelling and Machine Learning at IT University of Copenhagen (deadline March 20th)
by Stefan Heinrich 13 Feb '23

13 Feb '23

PhD position at IT University of Copenhagen, Denmark, starting in Summer 2023. Topic: Modelling hierarchical learning of music and speech processing. How does the human brain hierarchically process music or speech? It seems the brain is dynamically adapting to the timescales in the sensation in a way that components of music, such as melodies and low base lines are processed and integrated differently. Furthermore, it seems crucial that the brain is using a statistical learning scheme, thus learning this adaptation by how frequently these components occur. Despite a number of existing neuroimaging studies and scarce attempts to suggest underlying computational principles, research for detailed models is open. We plan modelling the learning of music by studying different computational mechanisms, both, more precise and w.r.t. its functionality close to specific biological neuron models, as well as more coarse, based on general computational principles such as hierarchical network structure, decoding schemes, and distributed activation. The computational research will be conducted side-by-side with a series of empirical EEG studies to verify the validity and further specify the models. The project is part of a cross-departmental initiative between the departments of computer science and digital design aimed at investigating machine-learning-based computational models of the human mind in relation to digital media interaction. Results from this project can enable understanding human information processing better, as well as applying derived computational principles in AI and machine learning approaches of the next generation. Application details: The ideal candidate should have a Masters in Computer Science, Computational Neuroscience, Developmental Psychology, Cognitive Science or related fields, as well as a strong interest in interdisciplinary research, at the intersection of Computational Modelling and Machine Learning. The salary scale will be in accordance with the Ministry of Finance’s agreement with the Danish Confederation of Professional Associations for a full-time position. ITU is a teaching and research-based tertiary institution concerned with information technology (IT) and the opportunities it offers. The University offers an informal working environment, a varied everyday life, and a highly motivated, competent, and 160 diverse international faculty. Copenhagen has a strong educational system, a rich cultural life, universal healthcare, good childcare, and a well-functioning infrastructure. The city is also among the world’s most liveable cities according to the Economist Global Liveability Index. Candidates will work together with Stefan Heinrich (stehe(a)itu.dk) and Paolo Burelli (pabu(a)itu.dk) and are encouraged to get in contact to develop the project details together. Link to apply and further application details: https://candidate.hr-manager.net/ApplicationInit.aspx?cid=119&ProjectId=181… Application deadline: 20 March 2023, at 23:59 CET. -- *************************** Dr. Stefan Heinrich Assistant Professor Computer Science Department IT University of Copenhagen https://stefanheinrich.net/ ***************************

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1ˢᵗ Advanced Scientific Programming in Python - Latin America in Mexico City, Mexico, 26 June – 1 July, 2023
by Jakob Jordan 13 Feb '23

13 Feb '23

ASPP-LatAm: 1st Advanced Scientific Programming in Python - Latin America ========================================================================= a Summer School by the ASPP faculty, the National Autonomous University of Mexico and the Secretarı́a de Educación, Ciencia, Tecnologı́a e Innovación de la Ciudad de México. https://latam.aspp.school Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are devised to be interactive and to give the students enough time to acquire direct hands-on experience with the materials. Students will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project — an entertaining computer game. We use the Python programming language for the entire course. Python works as a simple programming language for beginners, but more importantly, it also works great in scientific simulations and data analysis. We show how clean language design, ease of extensibility, and the great wealth of open source libraries for scientific computing and data visualization are driving Python to become a standard tool for the programming scientist. This school is targeted at Master or PhD students and Post-docs from all areas of science. Competence in Python or in another language such as Java, C/C++, MATLAB, or R is absolutely required. Basic knowledge of Python and of a version control system such as git, subversion, mercurial, or bazaar is assumed. Participants without any prior experience with Python and/or git should work through the proposed introductory material before the course. We are striving hard to get a pool of students which is international and gender-balanced. Date & Location ============= 26 June – 1 July, 2023. Mexico City, Mexico. Application ========= You can apply online: https://latam.aspp.school Application deadline: 23:59 UTC, Sunday March 12, 2023. There will be no deadline extension, so be sure to apply on time. Be sure to read the FAQ before applying: https://latam.aspp.school/wiki/faq Participation is for free, i.e. no fee is charged! Participants however should take care of travel, living, and accommodation expenses by themselves. We are in the process of securing some funds for supporting students with accommodation and living costs. Program ======= • Version control with git and how to contribute to open source projects with GitHub • Best practices in data visualization • Testing and debugging scientific code • Advanced NumPy • Organizing, documenting, and distributing scientific code • Advanced scientific Python: context managers and generators • Writing parallel applications in Python • Profiling and speeding up scientific code with Cython and numba • Programming in teams Tentative Faculty ================= • Aitor Morales-Gregorio, Theoretical Neuroanatomy, Institute of Neuroscience and Medicine, Forschungszentrum Jülich, Germany. • Carlos Cernuda, Data Analysis & Cybersecurity, Faculty of Engineering, Mondragon Unibertsitatea, Bilbao, Spain. • Jakob Jordan, Department of Physiology, University of Bern, Switzerland. • Jenni Rinker, Department of Wind Energy, Technical University of Denmark, Roskilde, Denmark. • Lisa Schwetlick, Experimental and Biological Psychology, Universität Potsdam, Germany. • Pamela Hathway, GfK, Nuremberg, Germany. • Pietro Berkes, NAGRA Kudelski, Lausanne, Switzerland. • Rike-Benjamin Schuppner, Institute for Theoretical Biology, Humboldt-Universität zu Berlin Germany. • Seetha Krishnan, Department of Neurobiology and Institute for Neuroscience, University of Chicago, Chicago, USA. • Tiziano Zito, Department of Informatics, Technische Universität Berlin, Germany. • Zbigniew Jędrzejewski-Szmek, Red Hat Inc., Warsaw Poland. Organizers ========== Head of the organization for ASPP-LatAm and responsible for the scientific program: • Carlos Echeverria Serur, Department of Psychology, Humboldt-Universität zu Berlin, Germany Organization team in Mexico: • Cristina Muzquiz Fragoso, DGTIC, Universidad Nacional Autónoma de Mexico • Miguel Angel Villanueva Velez, DGTIC, Universidad Nacional Autonoma de Mexico • Patricia Garces Natera, DGTIC, Universidad Nacional Autonoma de Mexico Website: https://latam.aspp.school Contact: latam(a)aspp.school

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New data management & sharing resources on the INCF portal!
by INCF 13 Feb '23

13 Feb '23

Data sharing is on everyone’s mind right now, especially since NIH put their data managing and sharing policy into effect on January 25. At INCF, we have been working to facilitate data sharing, reuse, and reproducibility in neuroscience since our inauguration in 2005. Our current focus is on developing, evaluating, and endorsing standards and best practices that facilitate data sharing, open, FAIR, and citable neuroscience, as well as providing the community with resources and training opportunities on how to implement these standards and best practices. We have just added new FAIR resources to our portal. Here is a summary of the resources INCF offers to researchers on the fundamentals of data sharing and data management: - The FAIR roadmap <http://bit.ly/FAIRRoadmapINCF> - The INCF Standards and Best Practices Portfolio <http://bit.ly/INCFportfolioSBPs> - The INCF Infrastructure Portfolio <http://bit.ly/INCFInfraPortfolio> - The INCF Training Suite <https://bit.ly/INCFTrainingSuite> - Community <https://www.incf.org/services/community-building> & capacity <https://www.incf.org/services/capacity-building> building - FAIR consulting services <https://www.incf.org/services/fair-consulting-services> Learn more <http://bit.ly/INCFsNewResources> about these resources INCF is a member organization - an active global network of neuroscientists, data scientists, and tool developers that come together to interact and receive feedback in order to solve large and small problems around data sharing and standardization. This network is our greatest resource and it’s open for participation: we have individual and group memberships, both for academic/non-profit groups and for companies in related fields. Many of our working groups are also open to new members. Want to get involved? Contact us at info(a)incf.org! /The INCF Team

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