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PhD and MSc Opportunities in Computational Neuroscience and Neuroimaging at the University of Toronto
by John Griffiths 23 Jan '20

23 Jan '20

The Whole Brain Modelling Group (PI Dr. John Griffiths; www.grifflab.com) at the CAMH Krembil Centre for Neuroinformatics ( www.krembilneuroinformatics.ca) and University of Toronto is looking for PhD and MSc students with a strong background in computational neuroscience and/or neuroimaging. The focus of the Group’s work is computational models of large-scale brain activity, with particular emphases on neural dynamics as measured by M/EEG and fMRI, oscillations, brain stimulation (TMS, TDCS), neural plasticity, and macro-connectomics. The student shall conduct research in one or more of these areas. They will have the opportunity to shape the details of the project based on their specific interests, as well as to contribute to other ongoing projects on a range of topics, including: neuroinformatics of whole-brain modelling, mapping and modelling anatomical connectivity and microstructure with DWI in relation to ageing and stroke, and multi-scale modelling of the thalamocortical system in relation to sleep, pharmacological neuromodulation, and neuropsychiatric disease. The successful candidate should have, minimally, an undergraduate degree in neuroscience, engineering, physics, mathematics, psychology, or related area, and a demonstrable track record of research experience and interest in computational neuroscience and/or neuroimaging. Expertise in one or more modern scientific computing programming language (Python, Matlab, Julia, R, C++) is essential. The candidate should also have familiarity with one or both of: i) neuroimaging data analysis (s/d/fMRI and/or M/EEG), and ii) computational modelling using numerical simulations (particularly modelling of neural population activity with mean-field/neural mass/neural field techniques, either with custom implementations or with tools such as The Virtual Brain Platform or Dynamic Causal Modelling). Full details of the position and application instructions can be found at www.grifflab.com/positions/ For informal inquiries, please email Dr. John Griffiths at john.griffiths(a)camh.ca with the title “PhD in Whole Brain Modelling” in the subject line ( Note: students interested in a September 2020 start at the University of Toronto should get in touch immediately to leave time for approaching application deadlines ) -- Dr. John D. Griffiths Independent Scientist @ Krembil Centre for Neuroinformatics, CAMH, Toronto Assistant Professor @ Department of Psychiatry, University of Toronto www.grifflab.com

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[publication and call for dialog] IEEE CIS Newsletter on Cognitive and Developmental Systems
by Pierre-Yves Oudeyer 23 Jan '20

23 Jan '20

Dear colleagues, we are happy to announce the release of the latest issue of the IEEE CIS Newsletter on Cognitive and Developmental Systems (open access). This is a biannual newsletter addressing the sciences of developmental and cognitive processes in natural and artificial organisms, from humans to robots, at the crossroads of cognitive science, developmental psychology, artificial intelligence, machine learning and neuroscience. It is available at: https://goo.gl/NAwBfD Featuring dialog: === "Curiosity as Driver of Extreme Specialization in Humans" == Dialog initiated by Celeste Kidd with responses from: Elizabeth Bonawitz, Maya Zhe Wang, Brian Sweis, Benjamin Hayden, Susan Engel, Abigail Hsiung, Shabnam Hakimi, Alison Adcock, Moritz Daum, Arjun Shankar, Tobias Hauser, Goren Gordon and Perry Zurn == Topic: Curiosity-driven learning is probably one of the most fundamental mechanisms in human learning, and yet it is also probably one of the least understood. Broadly construed as spontaneous exploration and engagement with activities or material without any extrinsic goal (as opposed to searching for information useful for an extrinsic goal), many mysteries remain to be uncovered. What are the causal links between curiosity and learning? How does prior knowledge about a topic or an activity relates to curiosity about this topic? What is the role of curiosity in life-span development? Can human curiosity explain the apparently unique tendency of humans for extreme specialization? Reversely, how do different forms of curiosity (diversive or specific) evolve as children grow up and become adults? While early computational models of curiosity propose theoretical approaches to understand their cognitive mechanisms, how can we understand the affective/ emotional dimensions of curiosity? And how has the linguistic concept of “curiosity” evolved in occidental culture? Call for new dialog: === « Leveraging Adaptive Games to Learn How to Help Children Learn Effectively" == Dialog initiated by George Kachergis == Topic: How can one achieve efficiently “translational educational sciences” and get these principles used in real-world large-scale educational technologies? In this dialog, Georges Kachergis highlights challenges related to collaborations between cognitive scientists and game developers, how to deploy real world experiments, and how to enable scientific understanding when many variables cannot easily be controlled? Those of you interested in reacting to this dialog initiation are welcome to submit a response by December 15th, 2018. The length of each response must be between 600 and 800 words including references (contact pierre-yves.oudeyer(a)inria.fr) Let us remind you that all issues of the newsletter are all open-access and available at: https://goo.gl/ZjjZNz I wish you a stimulating reading! Best regards, Pierre-Yves Oudeyer, Editor of the IEEE CIS Newsletter on Cognitive and Developmental Systems Research director, Inria Head of Flowers project-team Inria and Ensta ParisTech, France http://www.pyoudeyer.com Twitter: https://twitter.com/pyoudeyer and Fabien Benureau, Editorial Assistant Cognitive NeuroRobotics Unit, Okinawa Institute of Science and Technology 1919-1 Tancha, Onna, Okinawa Japan Email: fabien.benureau [at] oist [dot] jp

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UK PhD opportunities in Computational/Mathematical Biology or Neuroscience (EPSRC funded, 3.5 yrs, Sept 2020 start)
by James Rankin 23 Jan '20

23 Jan '20

*PhD in Computational/Mathematical Biology or Neuroscience (EPSRC funded, 3.5 yrs, Sept 2020 start) * There are a number projects proposed in Computational and Mathematical Biology or Neuroscience in the following call (follow Research Theme link to Mathematical biology and medicine). General information & apply (funding is primarily targeted at currently UK-based students): http://www.exeter.ac.uk/studying/funding/award/index.php?id=3830 Deadline is soon: 30th January. Contact: j.a.rankin(a)exeter.ac.uk or m.goodfellow(a)exeter.ac.uk

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postdoc position in reinforcement learning and decision making
by Gershman, Samuel Joseph 22 Jan '20

22 Jan '20

The Computational Cognitive Neuroscience Lab at Harvard University (Director: Sam Gershman) is seeking 1-2 postdoctoral fellows to work in the area of reinforcement learning and decision making. The start date is on or after October 1, 2020. The position is for 3 years. Requirements for this position are: (1) Experience with fMRI and/or human behavioral experiments. (2) A strong technical background in Bayesian and reinforcement learning models. Interested applicants should e-mail gershman(a)fas.harvard.edu<mailto:gershman@fas.harvard.edu> with a CV, statement of interest (not to exceed 2 pages), and a link to a publications page. For more information on the lab's research, please visit http://gershmanlab.webfactional.com/ Harvard is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.

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Phd position in perceptual decision making @ TU Darmstadt
by Jäkel, Frank 22 Jan '20

22 Jan '20

The Models of Higher Cognition group (PI: Frank Jaekel) at the TU Darmstadt Centre for Cognitive Science is looking for a PhD student in the area of perceptual decision making. In a joint DFG-project with the Neurophysiology group at the University of Mainz (PI: Maik Stuettgen) we are investigating neural and cognitive processes underlying criterion learning. We are looking for candidates who are interested in theory and modeling (signal detection theory, probabilistic models, reinforcement learning, neural networks) as well as psychophysical experiments in humans. Informal inquiries can be sent to jaekel(a)psychologie.tu-darmstadt.de<mailto:jaekel@psychologie.tu-darmstadt.de>. More information on the Models of Higher Cognition group can be found here: https://www.psychologie.tu-darmstadt.de/mhc and the full job ad is here: https://www.tu-darmstadt.de/universitaet/karriere_an_der_tu/stellenangebote…

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Two fully-funded PhD positions on infant neuroimaging and computational modelling at Trinity College Dublin, Ireland
by Lorijn Zaadnoordijk 22 Jan '20

22 Jan '20

Join us! Two PhD fully-funded scholarships are available to study the foundations of cognition using infant neuroimaging and computational modelling. Apply before Jan 31 for China Scholarship Council funding, or before Mar 1 for funding from our ERC FOUNDCOG project. How does the human mind develop? The FOUNDCOG team will address this question using neuroimaging of infants, in their critical first year after birth, to capture the development of the brain and its functions. We will interpret the results by comparing them to computational models of learning from artificial intelligence. In addition to characterising the development of the human mind, we aim to understand how it is disrupted by brain injury and to produce new diagnostic tools for neonatologists. 1) PhD Scholarship in Infant Neuroimaging, to start in September 2020 2) PhD Scholarship in Computational Modelling, to start in September 2020 · Includes fees, stipend and travel for 4 years, with funding from the ERC FOUNDCOG project · Excellent candidates from outside of the EU will also be considered · Selection will begin in March 2020, and the position will remain open until filled For more information, see: http://cusacklab.org/vacancies.html

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study abroad programs in Budapest
by Balazs Ujfalussy 22 Jan '20

22 Jan '20

Dear All: BSCS-US announces its two programs in Budapest for 2020. 1. Our regular program: BSCS - BUDAPEST SEMESTER IN COGNITIVE SCIENCE: FROM PHILOSOPHY TO NEUROSCIENCE will be held in the Fall of 2020, see http://www.bscs-us.org/ <http://www.bscs-us.org/>. Program start/end dates August 31 - December 4, 2020. Inquiry: bscs(a)bscs-us.org <mailto:bscs@bscs-us.org> 2. We have also a summer program Systems Neuroscience: a study abroad summer program http://www.sysneuro-semester.org/ <http://www.sysneuro-semester.org/> Program start/end dates June 15 - Aug 7, 2020 The BSCS Systems Neuroscience Program takes place at and academically supervised by the Department of Anatomy, Histology and Embryology, Semmelweis University Medical School, Budapest Inquiry: Péter Érdi (SysNeuro Director; BSCS Co-Director) perdi(a)kzoo.edu <mailto:perdi@kzoo.edu> bscs(a)bscs-us.org <mailto:bscs@bscs-us.org>

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Save the date! UK Neural Computation 2020 June 22nd-24th in Sheffield
by Hannes Saal 21 Jan '20

21 Jan '20

Save the date! We are pleased to announce the 2nd annual UK Neural Computation conference, June 22nd-24th 2020, at the University of Sheffield This is a national meeting for the UK community working on the computational side of neuroscience, which last year attracted more than 130 researchers. Same basic format as last year, so we will have modelling, maths, data science, theory, machine-learning, and all combinations thereof. Schedule: June 22nd: Tutorials and seminars for early career researchers June 23rd-24th: Main meeting Confirmed speakers for the main meeting: Rui Ponte Costa (Bristol) Dan Goodman (Imperial) Marc de Kamps (Leeds) Leah Krubitzer (UC Davis) Peggy Series (Edinburgh) Huiling Tan (Oxford) Yulia Timofeeva (Warwick) Mark Van Rossum (Nottingham) Keynote: David Willshaw (Edinburgh) For further details, see the website: http://neuralcomputation.uk/ Please look out for the abstract submission and registration announcement, coming soon. Hope to see you there! Hannes Saal (Sheffield) Robert Schmidt (Sheffield) Stuart Wilson (Sheffield) Mark Humphries (Nottingham)

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Industrial Ph.D. on Machine Learning in cognitive rehabilitation (La Rioja, Spain). Deadline January 31, 2020
by Asier Erramuzpe Aliaga 21 Jan '20

21 Jan '20

[Apologies for cross-posting] Industrial Ph.D. position on Machine Learning in cognitive rehabilitation (La Rioja, Spain) Neuronup is a leading company for cognitive rehabilitation working with several thousands of patients worldwide. More information at https://app.neuronup.com/assets/pdf/info/info_en_US.pdf and https://www.neuronup.com/en/ The Neuronup headquarters are located in Logroño, the capital of the region La Rioja, Spain. Logroño is a Northen city in Spain which is only 1.30h far from Bilbao-Basque Country, 1.50h from San Sebastian-Basque Country, 1h from Pamplona-Navarre Duration of the contract: 3 years, 40 h a week Gross salary: 24K EUR Cost of living in Logroño <https://www.numbeo.com/cost-of-living/in/Logro%C3%B1o-Logrono-Spain> Requisites (all the applicants must have): R1. Degree in Computer Science or Telecommunications Engineering R2. MSc in Computer Science or Telecommunications Engineering. R3. Average marks of first degree of 7.5/10 or higher. R4. Experience in Python and R R5. Have a permanent residence in Europe R6. C1 English Level The applicant will finalize an Industrial Ph.D. in Machine Learning in Health, funded by the CDTI-project "Digital solutions for rehabilitation and cognitive stimulation in neuropsychology" Tasks to perform during the Ph.D.: T1. Development of prediction models. T2. Classification and categorization of patients. T3. Model validation. T4. Multi-dimension data visualization T5. Integration of developed tools into the Neuronup database and search engine. *Interested applicants send an updated CV and two reference letters to neuronup(a)neuronup.com <neuronup(a)neuronup.com> before January 31, 2020*

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Deadline extension: Special Entropy Issue "Information Theory in Computational Neuroscience"
by Dimitrije Markovic 20 Jan '20

20 Jan '20

Dear Colleagues, We cordially invite you to submit a manuscript for possible publication in a Special Issue on "Information Theory in Computational Neuroscience" to be published in the journal Entropy (ISSN 1099-4300, IF 2.419, http://www.mdpi.com/journal/entropy) The aim of the Special Issue is to bring together neuronal models and neuronal plasticity mechanisms that are grounded in information theory principles, modern inference, and learning algorithms. We welcome submissions that use information theory as the basis for defining generative principles of neuronal dynamics over multiple spatio-temporal scales, which informs our understanding of information processing in the brain. You can see full details of the scope and submission details at: https://www.mdpi.com/journal/entropy/special_issues/Computational_Neuroscie… The new submission deadline is 31 March 2020. You may send your manuscript at any time before the deadline or a bit later. Submitted papers should not be under consideration for publication elsewhere. Entropy is fully open access. Open access (unlimited and free access by readers) increases publicity and promotes more frequent citations, as indicated by several studies. Please kindly note that an Article Processing Charge (APC) of CHF 1600 currently applies to all accepted papers. Fortunately, it is noticed that your institute have already had a central open access fund established in MDPI's Institutional Open Access Program, it means you do not have to pay the publication fees and your institute will cover it for you if you submit your papers to MDPI journals (see details at: <http://www.mdpi.com/about/ioap><http://www.mdpi.com/about/ioap>). You may contact your library and confirm this. Please do not hesitate to come back to us if there is anything further that we can help with. We look forward to hearing from you. Kind regards, Dimitrije Markovic and Claudius Gros ============================= Dr. Dimitrije Markovic Post-Doc at Technische Universität Dresden, Department of Psychology, Dresden, Germany Lab website: https://tu-dresden.de/mn/psychologie/ifap/ni Phone: +49-351-463-43146 Personal website: http://dimarkov.github.io/ =============================

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