January 2021 - Comp-neuro - lists.cnsorg.org

International Symposium on Artificial Intelligence and Brain Science 2020 Online
by Kenji Doya 09 Jan '21

09 Jan '21

We are going to hold an online symposium that brings together researchers in the forefront of AI and neuroscience. All talks will be made accessible as pre-recorded movies and we will have two-hour live discussion sessions on October 10-12, 2020. Registration is free and open till September 30. Please register from the web site below. ******** International Symposium on Artificial Intelligence and Brain Science http://www.brain-ai.jp/symposium2020/ Time below is in UTC (i.e., 10pm-0am Japan, 2pm-4pm UK, 9am-11am EDT, 6am-8am PDT) <Saturday, October 10th> 13:00 Get connected 13:15 Greetings: Kenji Doya (OIST) 13:30 Discussion on Keynote: Josh Tenenbaum (MIT) 14:00 Discussion on Session 1: Deep Learning and Reinforcement Learning Chair: Jun Morimoto (ATR) Discussant: Shunichi Amari (RIKEN) Speakers: Yann LeCun (NYU, Facebook), Yutaka Matsuo (U Tokyo), Doina Precup (McGill U) David Silver (DeepMind), Masashi Sugiyama (RIKEN AIP/U Tokyo IRCN) <Sunday, October 11th> 13:00 Discussion on Session 2: World Model Learning and Inference Chair: Hiroaki Gomi (NTT) Discussant: Mitsuo Kawato (ATR) Speakers: Ila Fiete (MIT), Karl Friston (UCL), Yukie Nagai (U Tokyo IRCN) Maneesh Sahani (Gatsby Unit), Tadahiro Taniguchi (Ritsumeikan U) 14:00 Discussion on Session 3: Metacognition and Metalearning Chair: Masayuki Matsumoto (Tsukuba U) Discussant: Keiji Tanaka (RIKEN) Speakers: Matthew Botvinick (DeepMind), Ryota Kanai (ARAYA), Angela Langdon (Princeton U) Hiroyuki Nakahara (RIKEN CBS), Xiao-Jing Wang (NYU) <Monday, October 12th> 13:00 Discussion on Session 4: AI for Neuroscience and Neuromorphic Technologies Chair: Takatoshi Hikida (Osaka U) Discussant: Kunihiko Fukushima (FLSI) Speakers: Jim DiCarlo (MIT), Yukiyaku Kamitani (Kyoto U), Rosalyn Moran (King’s College London) Terry Sejnowski (Salk Institute), Hidehiko Takahashi (Tokyo MDU) 14:00 Discussion on Session 5: Social Impact and Neuro-AI Ethics Chair: Masamichi Sakagami (Tamagawa U) Speakers: Anne Churchland (UCLA), Kenji Doya (OIST), Arisa Ema (U Tokyo IFI) Hiroaki Kitano (SONY CSL), Stuart Russell (UC Berkeley) Sponsor: KAKENHI Project on Artificial Intelligence and Brain Science (http://www.brain-ai.jp) Co-sponsors: RIKEN AIP (https://aip.riken.jp/?lang=en) U Tokyo IFI (https://ifi.u-tokyo.ac.jp/en/) U Tokyo IRCN (https://ircn.jp/en/) Contact: ncus(a)oist.jp ---- Kenji Doya <doya(a)oist.jp> Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University 1919-1 Tancha, Onna, Okinawa 904-0495, Japan Phone: +81-98-966-8594; Fax: +81-98-966-2891 https://groups.oist.jp/ncu

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Post Doc on AI and Behavior in London
by Dimitris Pinotsis 08 Jan '21

08 Jan '21

Post Doc on AI and Behavior in London The Computational Neuroscience and Psychiatry Lab (www.pinotsislab.com) at University of London—City is looking for a Post Doc with a strong background in AI/ Machine Learning and Behavioral Science. The Lab focuses on developing new algorithms for the analysis of behavioral data and human and animal brain imaging data. These are based on computational models of neural dynamics and state of the art machine learning techniques. Particular emphasis is put on applications in Computational Neuroscience and Psychiatry and developing models of human behavior and brain pathology. Also, the Lab develops brain theories that can explain brain function, using theoretical tools from deep neural networks and Bayesian brain theories. The lab also performs EEG recordings. The Post Doc shall conduct research at the intersection of human behavior and machine learning. She or he will build computational tools using state of the art machine learning algorithms. The position has an initial duration of 6 months. The successful candidate should have a PhD in machine learning, psychology, computational neuroscience, engineering or a related field. Expertise in one or more modern scientific computing programming language (Python, Matlab or R) is essential. Experience with large databases, SQL methods for data storage, web architectures and API development is an advantage. For informal inquiries, please email Dr. Dimitris Pinotsis at pinotsis(a)mit.edu

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PhD Studentships, University of Sussex, be.AI programme in Biomimetic Embodied AI
by Miguel Maravall 08 Jan '21

08 Jan '21

Dear colleagues The University of Sussex is offering 6 PhD studentships within its new Doctoral Scholarship Programme funded by the Leverhulme Trust. This programme in Biomimetic Embodied AI investigates how intelligence arises from the interaction of the brain with the body and the environment. It includes multiple projects that link between AI and Neuroscience: http://www.sussex.ac.uk/ccnr/be_ai/proposals. Please see below for the announcement (*deadline is 31st Jan 2021*). The University of Sussex invites applications for PhD studentships within the be.AI Leverhulme Doctoral Scholarship Programme (www.sussex.ac.uk/ccnr/be_ai<http://www.sussex.ac.uk/ccnr/be_ai>) which will bring together researchers from the humanities, life sciences and computing to pursue artificial intelligence (AI) in its original definition of understanding natural intelligence by emulating it in artificial systems. In our unique interdisciplinary centre, we will advance understanding of how the interaction between brain, body and environment gives rise to intelligence and how this insight can be used to build novel artificial intelligence. As a be.AI Scholar you will: * Be funded for 3.5 years with a tax free living allowance at the standard Research Council rate - currently £15,009 per year- and UK fees * Be eligible for generous financial support of up to £4,000 per year for training and research expenses, such as conference trips and experimental costs * Be eligible to apply for one of three 12 month postdoctoral research fellowships, available only to completing Leverhulme be.AI scholars * Benefit from supervision by world-leading researchers in many different aspects of AI * Benefit from taught courses in topics, such as ethics and data science. The Programme will fund three intakes of 6 students per year, starting in September 2021 (application deadline 31st January 2021). You will be registered within one of the participating schools (Life Sciences, Engineering and Informatics, Psychology, Philosophy, Media Film & Music) but will be encouraged to perform cross-disciplinary research with academics across Schools. In be.AI, you will work in a community of like-minded students and researchers supported by your own research seminars, invited lectures by world leading speakers, as well as student-led conferences and cohort building events. We are passionate about creating an interdisciplinary cohort of researchers, so we expect successful applicants to see beyond their disciplinary boundaries and embrace the opportunity to work at the intersection of multiple fields. For further details, including how to apply, see http://www.sussex.ac.uk/ccnr/be_ai Thanks! Miguel Prof Miguel Maravall (he/him) Director, Sussex Neuroscience Academic lead, Athena SWAN & gender equality, University of Sussex School of Life Sciences University of Sussex Falmer Brighton BN1 9QG United Kingdom http://www.sussex.ac.uk/lifesci/maravalllab/

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Postdoctoral Positions in Theoretical Neuroscience, Higher School of Economics, Moscow Russia FEB 14 DEADLINE
by boris gutkin 07 Jan '21

07 Jan '21

Post-doctoral position in Theoretical Neuroscience DEADLINE 14 February More Information: https://iri.hse.ru/theoretical_neuroscience2021 <https://iri.hse.ru/cognitive_neuroscience3> Application link: https://iri.hse.ru/polls/323647081.html <https://iri.hse.ru/polls/323647081.html> The Higher School of Economics Centre for Cognition & Decision Making <https://www.hse.ru/en/cdm-centre/> of the Institute of Cognitive Neuroscience in Moscow, Russia, invites applications for postdoctoral research positions in computational and mathematical approaches to understanding neural function and cognition at Theoretical Neuroscience Group (TNG). Research interests of the TNG at the Centre for Cognition and Decision Making are wide ranging, carried out in collaboration with the experimental labs at the Center. Current research topics include computational psychiatry, computational neuroeconomics, information processing in neurons and circuits, as well as role of oscillations in cognition. The candidate will have the opportunity to further define and expand the Group’s research programme. We are seeking highly qualified and motivated candidate with backgrounds in quantitative disciplines: applied mathematics, physics, computer science or engineering. Knowledge of biology, neuroscience and ability to work with data is highly desired. Candidates will be trained in model building, analysis and will be offered advanced training in neuroscience and cognitive psychology. Candidates will have an opportunity to develop independent research projects and collaborations under the direction of the group leading scientists. The TNG is a structural part of the HSE’s Centre for Cognition & Decision Making <https://www.hse.ru/en/cdm-centre/> with ample collaboration opportunities within the Centre with other research groups, both within Russia and internationally. This new international group is tightly linked with the Group for Neural Theory at the Ecole Normale Superior <http://iec-lnc.ens.fr/group-for-neural-theory/?lang=en> in Paris, where research internships and visiting positions can be made available. Application Process Applications must be submitted online. Please provide a CV, a statement of research interest and a recent research paper submitted via an online application form. At least two letters of recommendation should be sent directly to the International Faculty Recruitment Office at fellowship(a)hse.ru <mailto:fellowship@hse.ru> before the application deadline. Please note that direct applications to the hiring department may not be reviewed. More information can be also obtained from bgutkin(a)hse.ru <mailto:boris.gutkin@hse.ru>

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Fully funded doctoral position at Ecole Normale Superieure and CentraleSupelec Paris in AI/Cognitive Computational Neuroscience/Quantitative Finance from fall 2021
by boris gutkin 07 Jan '21

07 Jan '21

Fully funded doctoral position in multi-agent modelling of financial markets and cognitive computational neuroscience. Laboratory for Cognitive and Computational Neuroscience at the Ecole Normale Superieure Paris and the Chair for Quantitative Finance at CentraleSupelec are looking for exceptional candidates to work on a doctorate as a part of a collaborative project spanning development of multi-agent models of stock markets (e.g. see Lussange et al 2020, Bavard et al 2018, da Gamma Battista 2017) and the effects of human cognitive traits and bounded rationality on the market dynamics. The candidate will be physically based at ENS. The student will be advised by Damien Challet (Chair for Quantative Finance, CentraleSupelec) and Boris Gutkin (Mathematics of Neural Circuits Team, LNC2, ENS) and collaborate closely with Stefano Palminteri (Human Reinforcement Learning Team, LNC2, ENS). The student will have an opportunity to be involved in all aspects of the project, from computational modelling to behavioral experiments to data mining. Industrial applications of the project outcomes can also be explored as well as a potential collaboration with Capital Fund Management, Paris. More information can be found at: https://psl.eu/recherche/grands-projets-de-recherche/projets-europeens/prog… <https://psl.eu/recherche/grands-projets-de-recherche/projets-europeens/prog…> https://euraxess.ec.europa.eu/jobs/580403 <https://euraxess.ec.europa.eu/jobs/580403> Start expected in fall 2021. Elibigibility: Master’s degree or equivalent in a quantitative discipline. There is no nationality or age criteria, but applicants must not have resided or carried out their main activity (work, studies, etc.) in France for more than 12 months in the 3 years immediately before the deadline of the call Interested candidates should contact boris.gutkin(a)ens.fr <mailto:boris.gutkin@ens.fr> before January 30 to discuss their application to the program Bavard S, *Lebreton M, Khamassi M, Coricelli G, Palminteri S. Reference-point centering and range-adaptation enhance human reinforcement learning at the cost of irrational preferences <https://www.google.com/url?q=https%3A%2F%2Fwww.nature.com%2Farticles%2Fs414…>. Nature Communications (2018). da Gama Batista, Joao, Domenico Massaro, Jean-Philippe Bouchaud, Damien Challet, and Cars Hommes. "Do investors trade too much? A laboratory experiment." Journal of Economic Behavior & Organization 140 (2017): 18-34. Lussange, J., Lazarevich, I., Bourgeois-Gironde, S., Palminteri, S., Gutkin, B. (2020) Modelling Stock Markets by Multi-agent Reinforcement Learning. Comput Econ. https://doi.org/10.1007/s10614-020-10038- <https://doi.org/10.1007/s10614-020-10038->w

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Workshop 'Invention of Writing' (12-15/01)
by Andrea Santamaria 07 Jan '21

07 Jan '21

Dear Sir/Madam, We are delighted to announce our Workshop on the invention of writing, organised by the INSCRIBE Invention of Scripts and their Beginnings ERC project, based at the University of Bologna. It will start next Tuesday, 12th January and will run for four consecutive afternoons, until Friday the 15th January. The workshop is articulated into four thematic sessions and crosses boundaries between archaeology, linguistics, cognitive science, and much more. To join us, register here: https://us02web.zoom.us/webinar/register/WN_Wcibfgg_SRGkJVWJkE_NvA A single registration will allow you to access all sessions. For more information on our guest speakers and the full programme: https://www.inscribercproject.com/workshop//workshop_home.php Thank you and see you very soon! Silvia Ferrara

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Data Scientist Position in Bioinformatics and Neuroscience at Boston University
by Chen, Jerry 07 Jan '21

07 Jan '21

The Lab of Jerry Chen at Boston University is hiring a Staff-Level Data Scientist to be involved in several multi-year BRAIN Initiative related NIH and NSF funded projects. These projects focus on understanding cortical computation during behavior by combining behavior, genomics, spatial transcriptomics, anatomical reconstructions, and large-scale population recordings. This person will be involved in help to analyze experimental data, developing software tools to aid in the data analysis, and helping with data infrastructure and management. Specific Projects include: 1. Analysis of genomic data. 2. Image analysis for in situ sequencing of gene expression (ie. spatial transcriptomics) 3. Automated behavioral training and video analysis. 4. Analysis of dense electron microscope reconstructions of neuronal connectivity (ie. Connectomics). Required Skills: * BA/BS degree (MS/PhD preferred) in Computer Science, Mathematics, Engineering, Bioinformatics, Neuroscience or related technical field. * One to three years of academic or professional experience. * Programming experience in MATLAB, Python, and R is required. * Extensive background in either genomic analysis, image analysis, computer vision, or machine learning is preferred. If interested in applying, please submit a CV along with 3 references to jerry(a)chen-lab.org<https://mail.google.com/mail/?view=cm&fs=1&tf=1&to=jerry@chen-lab.org> Jerry Chen, PhD. Assistant Professor Department of Biology Boston University jerry(a)chen-lab.org<mailto:jerry@chen-lab.org> www.chen-lab.org

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Permanent position in computational modeling of neurostimulation in mental disorders
by Axel Hutt 07 Jan '21

07 Jan '21

------------------------------------------------------------------------------------ Permanent position in computational modeling of neurostimulation in mental disorders ------------------------------------------------------------------------------------ The research of the INRIA-team MIMESIS in Strasbourg / France (https://mimesis.inria.fr) aims to create a synergy between clinicians and scientists to develop new healthcare technologies. The team researchers collaborate closely with clinicians and choose their research focus along the clinical applications. Major scientific objectives are the development of advanced online- and offline simulations involving new numerical techniques for real-time computation and data-driven simulation dedicated to patient-specific modelling. One application branch is embedded in neuroscience with a specific focus on general anaesthesia and neurostimulation of patients suffering from mental disorders. For instance, members of MIMESIS work in the recently funded project A/D Drugs (https://www.inria.fr/en/ad-drugs-exploratory-action-aimed-optimising-neuros…) to develop novel neurostimulation techniques in psychosis that may emerge in schizophrenia patients. The team offers the possibility to apply for a permanent position as Chargé de Recherche (CR) or Directeur de Recherche (DR) in the research field of computational neuroscience with a strong focus on linking brain network modelling with experimental data. The new colleague should have a strong expertise in neurostimulation and/or modelling of experimental data observed in mental disorders. Strong programming and mathematical skills are mandatory. INRIA is a French National Institute for Research in Digital Science and Technology (https://www.inria.fr/en) with 8 research centres in France. The team MIMESIS is located in the centre of Strasbourg on the hospital campus as part of the Research Centre Nancy Grand Est. The application deadline will be mid of February 2021, but it is recommended to contact the team (by email: axel.hutt(a)inria.fr) in advance. For more details or sending your application documents (CV including publication list), please contact Dr. Axel Hutt (email: axel.hutt(a)inria.fr) .

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Postdoc in machine learning at EPFL (Lausanne, Switzerland)
by Milekovic Tomislav 06 Jan '21

06 Jan '21

Postdoc position in the lab of Prof. Gregoire Courtine at EPFL (Lausanne, Switzerland) Machine learning techniques to develop and enhance clinical treatments based on electrical stimulation of the spinal cord Location: The laboratory of Prof. Gregoire Courtine at the Swiss Federal Institute of Technology (EPFL) in Lausanne, Switzerland, is looking to fill a fully funded postdoc position. The qualified candidate will benefit from joining a very dynamic and multidisciplinary group working at the interface of computational neuroscience, neuroengineering, prosthetics and biology. EPFL provides state-of-the-art facilities and is one of the leading technical universities worldwide. Postdoc salaries at EPFL rank the highest in the world. Opportunity: The offered position will be based at the Defitech Center for interventional Neurotherapies (NeuroRestore) - a research and innovation center joining EPFL’s lab of Prof. Gregoire Courtine and the University Hospital of Lausanne (CHUV) lab of Prof. Jocelyne Bloch. NeuroRestore conceives, develops and applies medical therapies aimed to restore neurological functions. To this end, NeuroRestore integrates implantable neurotechnologies with innovative treatments developed through rigorous preclinical and clinical studies. By working with our network of vibrant high-tech start-ups and established medical technology companies, NeuroRestore is committed to validate our medical therapy concepts. The overarching goal of NeuroRestore is to see our medical therapies used every day in hospitals and rehabilitation clinics worldwide. Description: Therapies based on epidural electrical stimulation (EES) of the spinal cord can restore the ability to walk to people paralyzed by spinal cord injury, and alleviate gait deficits of people with Parkinson’s disease. EES does this by recruiting sensory axons within dorsal spinal roots that enter the spinal cord between the vertebrae to increase the activation of the spinal motor pools that, in turn, move the muscles. Yet, the efficacy of the EES-based therapies relies on synchronizing users’ movement intentions with the spatiotemporal stimulation protocols that reliably and accurately generate paralyzed movements. Due to the large state space of all the stimulation parameters (location, amplitude, frequency, etc.) efficacy of the therapy depends on the fast and accurate initialization of the stimulation protocols. As the patients use the stimulation, small movements of the array, as well as changes in spine position due to users’ posture can reduce the usability of the stimulation. Stimulation efficacy can be enhanced by dynamically adjusting the stimulation protocols to changes to the way how to users’ spinal cord reacts to stimulation. Finally, the functional use of the stimulation largely depends on the accurate timing of stimulation delivery. Machine learning approaches that infer users’ intentions based on behavioral, physiological or neural recordings can vastly improve the synchronization between intended and therapy-supported movements and, therefore, play a critical role in achieving functional recovery of patients. While the current medical devices mostly support block-based stimulation protocols that remain constant for hundreds of milliseconds, upcoming devices will enable changes of stimulation at a millisecond resolution, thus opening a new field for machine learning approaches that exploit these capabilities. The successful candidate will work to develop, implement and apply machine learning algorithms and approaches to enhance EES-based therapies. Specifically, he will: * Design the mapping procedures for the generation of transfer functions that relate the continuously-controlled stimulation to the evoked muscle activity. * Develop algorithms that automatically adjust these transfer functions as the interaction between patients and their EES-based therapy evolves. * Implement machine learning techniques that utilize users’ behavioral, physiological and neural signals to continuously synchronize the delivery of stimulation with the users’ movement intentions. * Lead the team that develops machine learning methods to initialize and adjust block-based EES protocols. * Assist and oversee the development and implementation of machine learning methods that use inference of discrete motor events to synchronize block-based EES protocols with the users’ intentions. By integrating well-equipped and expertly staffed rodent, non-human primate and clinical research facilities, NeuroRestore provides an ideal substrate for rapidly developing, integrating and clinically validating cutting-edge machine learning concepts within medical therapies, with the capacity to push successfully proven concepts into the technology transition phase. The successful candidate will have access to these animal platforms and will work within the framework of multiple NeuroRestore clinical trials with people with spinal cord injury and Parkinson’s disease. They will benefit from the possibility of validating their concepts in animal experiments and implementing them within the therapies being tested in the clinical trials. Prerequisites: · Doctoral degree (PhD) · Proficiency in Python, Matlab and C++ · Strong background in quantitative data analysis · Experience with applying multiple machine learning techniques to behavioral, physiological, biological and/or neural datasets · Good written and verbal skills in English Contact: Applications including a CV and a cover letter describing your background and interest should be sent to tomislav.milekovic(a)epfl.ch<mailto:tomislav.milekovic@epfl.ch>. Informal inquiries are welcome.

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Postdoc opportunity (fully funded): Theories and Models of Behaving Brains
by Ann Kennedy 05 Jan '21

05 Jan '21

The Kennedy lab (kennedylab.org<http://kennedylab.org/>) is hiring multiple fully-funded postdoctoral researchers for neural network modeling, data analysis, or deep learning projects. Our research goal is to develop new methods for analyzing and modeling high dimensional data, which we use to understand the structure of behavior, its control by the brain, and the dependence of brain activity and behavior on context, experience, and internal state. We work in close collaboration with experimental groups, with available projects studying neural encoding of state and behavior in basal ganglia, hippocampus, hypothalamus, and cortex. We are also pursuing pure theory projects, studying computation and dynamics in heterogeneous neural networks, inspired by the remarkable cell type diversity that has been uncovered throughout the brain via single-cell RNA sequencing experiments. We are a new theoretical neuroscience laboratory at Northwestern University, in the Physiology department of Feinberg Medical School on Chicago's Miracle Mile. Northwestern's Physiology department is ranked #3 in the US, and has an incredible concentration of expertise in the motor control and reward circuitry of the basal ganglia and cortex. Interested applicants, please email ann.kennedy(a)northwestern.edu<mailto:ann.kennedy@northwestern.edu> with a CV and a comment on your research interests.

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