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[news] Call for Participation - The Chef's Hat Cup @ IJCAI2021

by Pablo Vinicius Alves De Barros

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

June 3, 2021

PostDoc in Machine Hearing

by Sarah Verhulst

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

June 2, 2021

Research fellowships at the Univ. of Birmingham/UK

by Michael Biehl

*Two research fellowships at the * *Centre for Systems Modelling and Quantitative Biomedicine, College of Medical and Dental SciencesUniversity of Birmingham /UK **Full time, fixed term for 3.5 years* *Closing Date *27th June 2021. Online interviews will take place on 20th July 2021 For further details and information about how to apply visit *https://www.jobs.ac.uk/job/CGC736/research-fellows <https://www.jobs.ac.uk/job/CGC736/research-fellows> * (do not reply to this message, do not contact M. Biehl directly) The successful candidates will be educated to PhD level and have experience in one or more of the following areas: Position 1: mathematical models; complex networks, (nonautonomous) dynamical systems, bifurcation theory or numerical continuation. Having relevant experience in biology or medicine will be advantageous. Position 2: computational methods; machine learning, neural networks, data visualisation and analytics, artificial intelligence, Bayesian inference, or algorithm development. Having relevant aligned experience in biology, medicine, or wearable technologies will be advantageous. -- ---------------------------------------------------------- Prof. Dr. Michael Biehl Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence P.O. Box 407, 9700 AK Groningen The Netherlands Tel. +31 50 363 3997 https://www.cs.rug.nl/~biehl m.biehl(a)rug.nl

June 2, 2021

EITN workshop on "Computational Neuroscience in EBRAINS", 10 june 2021

by Zélie Tournoud

Dear colleagues, We are happy to invite you to attend to the EITN (European Institute for Theorethical Neuroscience) workshop on "Computational Neuroscience in EBRAINS" taking place online on *June 10th, 2021, starting from 13:00 CEST*. Attendance is free and open to everyone upon registration, feel free to share the event to your collaborator who might be interested in the topic. To automatically receive your access link by email before the event, *register online* on this page: Register to the Zoom meeting <https://zoom.us/meeting/register/tJ0vd-CoqzkoHNTvv9UhOQ0Qbnex9MikG2F1>. The detailled program is available on this page <https://www.eitn.org/index.php/calendar-event/eventdetail/744/-/workshop-on…> that will be kept updated. * *Description of the workshop:* Organized by Andrew Davison (CNRS), Viktor Jirsa (AMU) and Alain Destexhe (CNRS). EBRAINS is a open-access platform built by the Human Brain Project and which provides tools for various applications in neuroscience. The aim of this workshop is to introduce some of the EBRAINS tools that are of particular interest for applications in computational neuroscience. These tools provide help to simulate models, from the cellular to the whole-brain level. Each tool will be introduced, then a "live demo" will be provided to demonstrate its use. As a companion to this workshop, we plan to provide recordings of each session on a YouTube channel, as well as scripts that were used in for the live demos. * *List of speakers:* Egidio d'Angelo (Pavia) Claudia Casellato (Pavia) Florent Bonnier (CNRS) Petrut Bogdan (U Manchester) Andrew Davison (CNRS) Alain Destexhe (CNRS) Timo Dickscheid (Jülich) Jan Fousek (AMU) Alice Geminiani (Pavia) Jennifer Goldman (CNRS) Brent Huisman (Jülich) Viktor Jirsa (AMU) Carmen Lupascu (CNR) Armando Romani (BBP/EPFL) Michael Schirner (Charité) Sam Yates (CSCS) We look forwards on seeing you on the 10th of June! Thank you and have a great day, /The EITN Team/

June 2, 2021

[Journals] 2nd CFP: Special Issue on "Theory of Mind in Humans and in Machines"

by Bogdan Ionut Cirstea

Dear colleagues, Apologies for cross-posting. Together with Prof. Fabio Cuzzolin (Oxford Brookes University, UK), Prof. Barbara Jacquelyn Sahakian (University of Cambridge, UK) and Dr. Christelle Langley (University of Cambridge, UK), we are organizing a special issue (Frontiers Research Topic) on the emerging topic of "Theory of Mind in Humans and in Machines" under the "Frontiers in Artificial Intelligence" and "Frontiers in Computational Neuroscience" journals. We would like to invite you to contribute articles to the Research Topic. For more information on this special issue, please visit the website at https://www.frontiersin.org/research-topics/16802/theory-of-mind-in-humans-… Papers may be submitted until the 30th of July 2021 (manuscript submission extended deadline). Submitted papers should not be under consideration for publication elsewhere. We also encourage authors to send a short abstract (via the platform) to ensure compliance with the topic and scope of the Frontiers journals as early as possible. Topics of interest include, but are not limited to, theoretical proposals, computational experiments, and case studies of: • Computational Theory of Mind • Learning from Demonstrations • Cognitive Models for Learning from Demonstration and Planning • Neuroscience-inspired models of Theory of Mind • Human-Robot Interaction • Cooperative Inverse Reinforcement Learning (assistance games) • Learning from Preferences If you intend to send an article to the special issue, please do let us know by hitting the "Participate" button in the web interface. If you have any questions or need any kind of assistance from us, please do not hesitate to let us know. On behalf of the topic editors, -- Bogdan-Ionut Cirstea Topic Editors: Prof. Fabio Cuzzolin, Oxford Brookes University, UK < fabio.cuzzolin(a)brookes.ac.uk> Prof. Barbara Jacquelyn Sahakian, University of Cambridge, UK < bjs1001(a)cam.ac.uk> Dr. Bogdan-Ionut Cirstea, Oxford Brookes University, UK < bcirstea(a)brookes.ac.uk> Dr. Christelle Langley, University of Cambridge, UK <cl798(a)medschl.cam.ac.uk >

June 1, 2021

Evolving Neural Networks workshop

by manuel molano

Dear all, We are glad to announce the 1st Evolving Neural Networks Workshop (June 17, 2021). The goal of the workshop is to bring together experts from Systems and Computational Neuroscience, Machine Learning and the Evo-Devo field to discuss if and how knowing the evolutionary history of neural circuits can help us understand the way the brain works, as well as the relative importance of learned VS innate neural mechanisms. We have a great list of speakers from the fields of Systems and Computational Neuroscience, Machine Learning and Evolutionary Developmental (Evo-Devo) biology. If you are interested REGISTER HERE<https://docs.google.com/forms/d/e/1FAIpQLSfO69TaE5Tk4eUysh4eCnJ7tlJYRTCcE_m…>, it is free! For more information visit our webpage<https://sites.google.com/view/evolving-nns/home> or contact evolvingneuralnetworks(a)gmail.com<mailto:evolvingneuralnetworks@gmail.com> We hope to see you soon! SCHEDULE (Eastern Time) 8-8.10 Intro 8.10-8.35 Pamela Lyon What basal cognition can do for you (neuroscientists) 8.35-9.00 Luis Puelles Brain evolution crosses an ontogenetic 'ant's country' that escapes analysis 9.00-9.25 Paul Cisek The evolution of the human brain, long before humans 9.25-9.50 Robert Yang Evolving the Olfactory System with Machine Learning 09.50-10.20 Discussion 10.20-10.40 Break 10.40-10.50 Intro 10.50-11.15 Linda Wilbrecht Considering contextual factors at acute and evolutionary timescales in the study of learning and decision making 11.15-11.40 Ida Momennejad TBA 11.40-12.05 Dayu Lin Neural mechanisms of aggression 12.05-12.30 Tony Zador Learning through the Genomic Bottleneck 12.30-13.00 Discussion

June 1, 2021

Job: Engineer in MEG-EEG signal processing and open-source software development

by Franco Pestilli

The Paris Brain Institute is recruiting a motivated individual to join the *MEEGbrainlife* project, introducing MEG and EEG data processing pipelines on the open-access brainlife.io cloud computing platform. This is a 18-24 months contract funded jointly by the French ANR and the American NIH under the international program call « Collaborative Research in Computational Neuroscience » (CR‐CNS). The successful candidate will be responsible for planning, developing, and maintaining *MEG‐EEG data processing Apps into brainlife.io <http://brainlife.io/>* and *contribute to innovative research projects* on the platform. In close collaboration with the expert members of the MEEGbrainlife consortium, he/she will define data specifications, code architecture, data and code output quality check procedures to set the groundwork for the rapid development of a full data processing pipeline for MEG‐EEG data into brainlife.io. *More information and contact* for the application available here: https://owncloud.icm-institute.org/index.php/s/MBrIpIFcH3F9lV5 *FRANCO PESTILLI*, *Ph.D.* | *Associate Professor* Department of Psychology <https://liberalarts.utexas.edu/psychology/index.php> | College of Liberal Arts <https://liberalarts.utexas.edu/> | The University of Texas at Austin <https://www.utexas.edu/> he/him | pestilli(a)utexas.edu | web <https://liberalarts.utexas.edu/psychology/faculty/fp4834> | GitHub <https://github.com/francopestilli> | brainlife.io CONFIDENTIALITY NOTICE: This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message.

May 31, 2021

pre- and post-doc neuromorphic fellowships at the Sevilla Microelectronics Institute

by bernabe

Dear all, The Neuromorphic group at IMSE (Sevilla Microelectronics Institute, Spain) wellcomes candidates to apply for pre- and post-docs fellowships on neuromorphic engineering. Please visit our web-site at www.imse-cnm.csic.es/neuromorphs to find out about our running projects, activities, and publications. More details on the fellowships (duration/salary/contact) is given at: http://www2.imse-cnm.csic.es/neuromorphs/index.php/News-and-position-openin… cheers, -- Bernabe Linares-Barranco, Director Instituto de Microelectrónica de Sevilla (IMSE-CNM), CSIC, Sevilla, Spain

May 31, 2021

Job opening: Research Scientist - Computational Neuroscience and Machine Learning/AI

by Michiel Remme

Dear Colleagues, Our startup INAIT, based in Lausanne, Switzerland, is seeking a permanent and full-time Research Scientist at the intersection of computational neuroscience and machine learning/AI. Are you interested in developing new machine learning/AI methods based on neuroscientific insights, and apply them to business problems? Then come join us! Major duties and responsibilities: * Contribute to the research and development of the next generation of neuroscience-inspired machine learning/AI methods * Contribute to the development of computational models of detailed and/or simplified neuronal networks * Work closely with a team of computational neuroscientists, machine learning engineers and software developers towards business solutions Essential skills and experience required: * PhD in computational neuroscience or related field (or equal experience: Masters and 4+ years of research experience) * Research involving learning and/or dynamics in rate-based and/or spiking neural networks * Experience in machine learning using frameworks such as scikit-learn, PyTorch or TensorFlow * Successful publication record * Experience in Python code development * Experience using UNIX/Linux operating systems * Excellent team player * Fluent spoken and written English Preferred: * Experience with a computational neuroscience simulation framework such as NEST, NEURON or Brian * Experience in scientific computing on shared and/or distributed parallel machines * Experience in the software development life-cycle including unit testing, continuous integration, version control, debugging and documentation * Successful track record in designing, developing and maintaining software projects Where: Lausanne, Switzerland Start date: As soon as possible Activity rate: 100% Duration of contract: CDI Competitive salary & benefits Cutting edge research, Positive work environment, Hybrid work model (combination of WFH and work from the office) For applications visit apply.workable.com/inait<http://apply.workable.com/inait/> INAIT SA https://www.inait.ai<https://www.inait.ai/> Avenue du Tribunal Fédéral 34 1005 Lausanne Switzerland

May 30, 2021

Call for papers for MLCN2021 workshop at MICCAI 2021

by MLCN Workshop

*Please find below the call for papers for the International Workshop of Machine Learning in Clinical Neuroimaging (MLCN) which is held virtually on the 27th of September 2021 at MICCAI 2021 in Strasbourg, France. We welcome contributions to novel machine learning methods and their applications to clinical neuroimaging data.* The submission deadline is *25 June 2021*, and all MLCN accepted papers will be eligible for the best paper award of 500 USD. For more information, please visit https://mlcnws.com/call-for-papers/*.* Best wishes, The MLCN 2021 steering and organizing committees Christos Davatzikos, Andre Marquand, Jonas Richiardi, Emma Robinson Ahmed Abdulkadir, Mohamad Habes, Seyed Mostafa Kia, Vinod Kumar, Jane Maryam Rondina, Chantal Tax, Thomas Wolfers ================================================================================================ Call for Papers The International Workshop of Machine Learning in Clinical Neuroimaging ( https://mlcnws.com/) a satellite event of MICCAI (https://miccai202 <https://miccai2021.org/>1 <https://miccai2020.org/>.org <https://miccai2021.org/>), calls for original papers in the field of clinical neuroimaging data analysis with machine learning. The two tracks of the workshop include methodological innovations as well as clinical applications. This highly interdisciplinary topic provides an excellent platform to connect researchers of varying disciplines and to collectively advance the field in multiple directions. In the machine learning track, we seek novel contributions that address current methodological gaps in analyzing high-dimensional, longitudinal, and heterogeneous clinical neuroscientific data using stable, scalable, and interpretable machine learning models. Topics of interest include but are not limited to: - Big data - Spatio-temporal brain data analysis - Structural data analysis - Graph theory and complex network analysis - Longitudinal data analysis - Model stability and interpretability - Model scalability in large neuroimaging datasets - Multi-source data integration and multi-view learning - Multi-site data analysis, from preprocessing to modeling - Domain adaptation, data harmonization, and transfer learning in neuroimaging - Unsupervised methods for stratifying brain disorders - Deep learning in clinical neuroimaging - Model uncertainty in clinical predictions - … In the *clinical neuroimaging *track*,* the applications of existing machine learning algorithms are evaluated to move towards precision medicine for complex brain disorders. The discovery of biological markers in medicine is an important challenge across different fields and various experimental procedures and designs are used to detect biological signatures that can be utilized for improvement in diagnostic, treatment, or for other beneficial ends. However, for most complex brain disorders, we do not have reliable biomarkers today. The application of advanced machine learning methods may help to reach this goal. Therefore, we invite the community to submit conference contributions on machine learning approaches with the goal to improve our understanding of complex brain disorders, moving the field closer towards precision medicine. Topics of interest include but are not limited to: - Biomarker discovery - Refinement of nosology and diagnostics - Biological validation of clinical syndromes - Treatment outcome prediction - Course prediction - Analysis of wearable sensors - Neurogenetics and brain imaging genetics - Mechanistic modeling - Brain aging - The presentation of clinical neuroimaging databases to stimulate developments in machine learning - … ------------------------------ Submission Process: The workshop seeks high-quality, original, and unpublished work that addresses one or more challenges described above. Papers should be submitted electronically in Springer Lecture Notes in Computer Science (LCNS) style (see https://miccai2021.org/en/PAPER-SUBMISSION-GUIDELINES.html for detailed author guidelines) using the CMT system at https://cmt3.research.microsoft.com/MLCN2021. The page limit is 8-pages (text, figures, and tables) plus up to 2-pages of references. We review the submissions in a double-blind process. Please make sure that your submission is anonymous. Accepted papers will be published in a joint proceeding with the MICCAI 2021 conference. ------------------------------ MLCN Special Issue at the MELBA journal: This year, we will invite the top accepted papers to submit an extended version of their contribution to the MLCN special issue at the Journal of Machine Learning for Biomedical Imaging (MELBA) <https://www.melba-journal.org/about>. The invited papers will go through an independent review process by the journal. ------------------------------ Best Paper Award: All MLCN accepted papers will be eligible for the best paper award. The recipient of the award will be chosen by the MLCN scientific committee based on the scientific quality, novelty, and clarity of contributions. The winner will be announced at the end of the workshop and will receive a 500 USD honorarium. ------------------------------ Important Dates: - Paper submission deadline: June 25, 2021, 11:59 PM Pacific Time - Notification of Acceptance: July 16, 2021 - Camera-ready Submission: July 30, 2021 - Workshop Date: September 27, 2021

May 30, 2021