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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

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

Jan. 7, 2021

Workshop 'Invention of Writing' (12-15/01)

by Andrea Santamaria

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

Jan. 7, 2021

Data Scientist Position in Bioinformatics and Neuroscience at Boston University

by Chen, Jerry

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

Jan. 7, 2021

Permanent position in computational modeling of neurostimulation in mental disorders

by Axel Hutt

------------------------------------------------------------------------------------ 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) .

Jan. 7, 2021

Postdoc in machine learning at EPFL (Lausanne, Switzerland)

by Milekovic Tomislav

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.

Jan. 6, 2021

Postdoc opportunity (fully funded): Theories and Models of Behaving Brains

by Ann Kennedy

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.

Jan. 5, 2021

Postdoc Position - Human Intracerebral Speech Perception

by Lori Holt

Interested to join a highly collaborative, vibrant research environment in Pittsburgh? We are seeking to understand how the brain flexibly maps speech input across manipulations in short-term input regularities. The postdoctoral position will be supported by a new NIH-sponsored research project, *Flexible representation of speech in the supratemporal plane*, that weds the joint expertise of Lori Holt (Carnegie Mellon University) and Taylor Abel (Pediatric Neurosurgery, University ofPittsburgh) to advance how dynamic, flexible aspects of the mapping of speech input to phonemes are represented in the intracerebral response of human cortex measured with stereoelectroencephalography. You can find more info here: https://www.cmu.edu/dietrich/psychology/holtlab/PDF/cmupittpostdocad2020.pdf Please feel free to be in touch with questions for Lori (loriholt(a)cmu.edu) or Taylor (abeltj(a)upmc.edu) ______________________________________________________________ loriholt Professor, Department of Psychology | Neuroscience Institute | Center for the Neural Basis of Cognition Carnegie Mellon University loriholt(a)cmu.edu | www.psy.cmu.edu/~holtlab/ pronouns: she, her, hers

Jan. 5, 2021

Digital Info Day - International Master & PhD in Computational Neuroscience @ BCCN Berlin - 27.01.21

by Graduate Programs

Dear Computational Neuroscientists, Please share the following event information with anyone who may be interested. We at the Bernstein Center for Computational Neuroscience (BCCN) Berlin will hold a "Digital Info Day" to discuss our International Master & Doctoral Programs in Computational Neuroscience on Wednesday, January 27th, at 3pm (CET). The event will consist of talks by: * Prof. Dr. Klaus Obermayer (head of the programs) * Lisa Velenosi (teaching coordinator) * Current master and doctoral students Attendees will also have the opportunity to meet & discuss with current students and ask any questions or concerns that they may have. See our website <https://www.bccn-berlin.de/events-list/information-day-international-gradua…> for a more detailed schedule and registration link. Best regards and happy new year, Lisa Velenosi -- Lisa Velenosi Teaching Coordinator Bernstein Center for Computational Neuroscience Humboldt-Universität zu Berlin Philippstraße 13, Haus 6; 10115 Berlin; Germany Tel: +49 (0)30 2093 6773 Technische Universität Berlin Marchstraße 23; Raum 5.061; 10587 Berlin; Germany Tel: +49 (0)30 314 72006 SFB1315 - Network Outreach Coordinator PhD & Postdoc Cohort

Jan. 5, 2021

NEURAL COMPUTATION - December 1, 2020

by Terry Sejnowski

Neural Computation - Volume 32, Number 12 - December 1, 2020 available online for download now: http://www.mitpressjournals.org/toc/neco/32/12 http://cognet.mit.edu/content/neural-computation ----- Articles Resonator Networks Outperform Optimization Methods at Solving High-dimensional Vector Factorization Spencer Kent, E. Paxon Frady, Friedrich T Sommer, and Bruno A. Olshausen Resonator Networks for Factoring Distributed Representations of Data Structures E. Paxon Frady, Spencer Kent, Bruno A. Olshausen, and Friedrich T Sommer Differential Covariance: A New Method to Estimate Functional Connectivity in fMRI Tiger W. Lin, Yusi Chen, Qasim Bukhari, Giri P. Krishnan, Maxim Bazhenov, and Terrence J. Sejnowski Letters Synchrony and Complexity in State-related EEG Networks: An Application of Spectral Graph Theory Amir Hossein Ghaderi, Bianca R. Baltaretu, Masood Nemati Andevari, Vishal Bharmauria, and Fuat Balci Toward a Unified Framework for Cognitive Maps Woori Kim, Yongseok Yoo Active Learning for Level Set Estimation Under Input Uncertainty and Its Extensions Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, and Ichiro Takeuchi Redundancy-aware Pruning of Convolutional Neural Networks GuoTian Xie Analyzing and Accelerating the Bottlenecks of Training Deep SNNs With Backpropagation Ruizhi Chen, Ling Li ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs(a)mit.edu ------------

Jan. 4, 2021

WorldWideNeuRise, an online seminar series promoting early-career researchers

by William Podlaski

We are very pleased to announce the new seminar series WWNeuRise that explicitly targets PhD students and postdocs (https://neurise.github.io/) WWNeuRise aims to give early career scientists an opportunity to share their exciting work with a large audience and make connections with people interested in similar questions. The seminar series will be hosted on WWNeuro and sponsored by eLife. The first seminar block, entitled "Neuroscience at the intersection of experiment and theory", will start in January 2021 and features six exciting talks by Nicolas Meirhaeghe (Jazayeri lab, MIT) Federico Stella (Battaglia lab, Donders Institute) Soledad Gonzalo Cogno (Moser lab, NTNU) Zoe Ashwood (Pillow lab, Princeton University) Claire Hales (Robinson lab, University of Bristol) Arseny Finkelstein (Svododa lab, Janelia HHMI) For more information, please visit the WWNeuRise website ( https://neurise.github.io/) or twitter (https://twitter.com/WWNeuRise) We are looking forward to seeing you all in January! The organising committee, Ellen Boven (Apps lab, U Bristol) Christina Buetfering (Häusser lab, U College London) Lucie Descamps (Kentros lab, NTNU) Gily Ginosar (Ulanovsky lab, Weizmann Institute) Loreen Hertäg (Sprekeler lab, TU Berlin) Joram Keijser (Sprekeler lab, TU Berlin) Bill Podlaski (Machens lab, Champalimaud)

Jan. 4, 2021