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Assistant Professor / Lecturer position with Machine Learning focus
by Peter Andras 02 Jun '20

02 Jun '20

Lecturer in Data Science (Education & Research) (equivalent of tenure-track Assistant Professor) with Machine Learning focus Keele University - School of Computing and Mathematics Location: Keele Salary: £42,783 to £52,560 Grade 8 Hours: Full Time Contract Type: Permanent Placed On: 18th May 2020 Closes: 17th June 2020 Job Ref: KU00001483 <https://people.keele.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VAC ANCY_ID%3d864042LDgx%1BUSESSION=&WVID=0493472Nsk&LANG=USA> <https://people.keele.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VAC ANCY_ID%3d864042LDgx%1BUSESSION=&WVID=0493472Nsk&LANG=USA> Faculty of Natural Sciences School of Computing and Mathematics Salary: Grade 8, £42,783 - £52,560 Keele University is renowned for its exciting approach to higher education, innovative research, beautiful campus, strong community spirit and excellent student experience. With a turnover in excess of £170 million, over 10,000 students and a total staff of approximately 2000, the University provides high quality teaching across a wide range of academic and vocational subjects and promotes world-class research. Further information can be found at <http://www.keele.ac.uk/> http://www.keele.ac.uk. This post represents an exciting opportunity for an ambitious individual to join a team of excellent academics in Keele Universitys Faculty of Natural Sciences. The Faculty is responsible for research and teaching in many areas of computer science, mathematics, and the physical and biological sciences. Applications are welcome from enthusiastic individuals committed to high quality teaching and research in any relevant field of Computer Science but in particular areas that complement data science such as data analytics, artificial intelligence, machine learning, visualisation, and statistics, and who have interests that complement our existing research strengths while broadening the scope of our teaching expertise. The lectureship post is part of continued growth and expansion of Computer Science at Keele, which presents many new opportunities for the development of synergies in both teaching and research. The successful candidate will be expected to lead the delivery of a new MSc programme in Artificial Intelligence and Data Science ( <https://www.officeforstudents.org.uk/news-blog-and-events/press-and-media/f unding-boost-for-new-courses-in-artificial-intelligence-and-data-science/> funded by the Office for Students) and develop an active research programme that both complements and extends our existing research profile in Computer Science. Candidates are also expected to develop research collaborations with colleagues at Keele and elsewhere in strategic research areas of the University, such as smart energy, big data, global health or social inclusion. Details of the research carried out in Computer Science at Keele can be found <https://www.keele.ac.uk/scm/research/computerscienceresearch/> https://www.keele.ac.uk/scm/research/computerscienceresearch/. The successful candidate will have a PhD in an appropriate area of Computer Science (or be very close to completion of his/her PhD) and will have a strong commitment to delivering high quality undergraduate and postgraduate teaching, including supervision of undergraduate and postgraduate research projects and the development and delivery of new modules and programmes. The post-holder will have the skills, enthusiasm and flexibility for teaching across a wide range of computer science topics and will also contribute to recruitment activities and administrative duties within our Computer Science programmes. Informal enquires can be made to Professor Peter Andras on 01782 733412 or <mailto:p.andras@keele.ac.uk> p.andras(a)keele.ac.uk. The University is committed to operating flexible working practices wherever possible. Keele University values equality and diversity across our workforce and to ensuring our staff community is reflective of the diversity of our student population. In support of these commitments the University welcomes applications from individuals of Black, Asian and ethnic minority backgrounds for all roles. Keele University is committed to the principles of the Athena SWAN charter, and values equality and diversity across our workforce. We strive to ensure that our workforce is representative of broader society, and therefore, we would actively welcome applications from women for this role. For full post details please visit: <http://www.keele.ac.uk/vacancies> www.keele.ac.uk/vacancies Keele University employees wishing to apply should login to Employee Self Service and click on the 'View current vacancies' link. Closing date for applications: 17th June 2020 Post reference: KU00001483

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Assistant Professor / Lecturer position
by Peter Andras 02 Jun '20

02 Jun '20

Lecturer in Data Science (Education & Research) (equivalent of tenure-track Assistant Professor) Keele University - Faculty of Natural Sciences - School of Computing and Mathematics Location: Keele Salary: £42,793 to £51,034 Hours: Full Time Contract Type: Permanent Placed On: 20th May 2020 Closes: 17th June 2020 Job Ref: KU00001484 <https://people.keele.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VAC ANCY_ID%3d445276LDkO%1BUSESSION=&WVID=0493472Nsk&LANG=USA> <https://people.keele.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VAC ANCY_ID%3d445276LDkO%1BUSESSION=&WVID=0493472Nsk&LANG=USA> Salary: Grade 8, £42,793 - £51,034 Keele University is renowned for its exciting approach to higher education, innovative research, beautiful campus, strong community spirit and excellent student experience. With a turnover in excess of £170 million, over 10,000 students and a total staff of approximately 2000, the University provides high quality teaching across a wide range of academic and vocational subjects and promotes world-class research. Further information can be found at <http://www.keele.ac.uk/> http://www.keele.ac.uk. This post represents an exciting opportunity for an ambitious individual to join a team of excellent academics in Keele Universitys Faculty of Natural Sciences. The Faculty is responsible for research and teaching in many areas of computer science, mathematics, and the physical and biological sciences. Applications are welcome from enthusiastic individuals committed to high quality research and teaching in any relevant field of Mathematical or Statistical Data Science (e.g. statistics, mathematical artificial intelligence, mathematical machine learning, statistical data science, computational data science but not restricted to these particular fields, although the preference is a field in Pure Mathematics), and who have interests that complement our existing research strengths while broadening the scope of our research and teaching expertise. The lectureship post is part of continued growth and expansion of Data Science and Mathematics at Keele, which presents many new opportunities for the development of synergies in both teaching and research. The successful candidate will be expected to develop an active research programme that both complements and extends our existing profile in Data Science, Mathematics and Statistics. Candidates are also expected to develop research collaborations with colleagues at Keele and elsewhere in strategic research areas of the University, such as smart energy, big data, global health or social inclusion. Information about the Mathematics and Statistics research context or Computer Science research context at Keele can be found at: <https://www.keele.ac.uk/scm/research/mathematicsresearch/> https://www.keele.ac.uk/scm/research/mathematicsresearch/ <https://www.keele.ac.uk/scm/research/computerscienceresearch/> https://www.keele.ac.uk/scm/research/computerscienceresearch/ The successful candidate will have a PhD in an appropriate area of Mathematical, Statistical or Computer Science (or be very close to completion of their PhD) and will have a strong commitment to delivering high quality undergraduate and postgraduate research and teaching, including supervision of undergraduate and postgraduate research projects and the development and delivery of new modules. The post-holder will have the skills, enthusiasm and flexibility for teaching across a wide range of Data Science, Mathematics and Statistics topics and will also contribute to recruitment activities and administrative duties within our Data Science programmes. Informal enquires can be made to Professor Peter Andras on 01782 733412 or <mailto:p.andras@keele.ac.uk> p.andras(a)keele.ac.uk Keele University is committed to the principles of the Athena SWAN charter, and values equality and diversity across our workforce. We strive to ensure that our workforce is representative of broader society, and therefore, we would actively welcome applications from women for this role. The University is committed to operating flexible working practices wherever possible. Keele University values equality and diversity across our workforce and to ensuring our staff community is reflective of the diversity of our student population. In support of these commitments the University welcomes applications from individuals of Black, Asian and ethnic minority backgrounds for all roles. For full post details and to find out more about working at Keele please visit: <http://www.keele.ac.uk/vacancies> www.keele.ac.uk/vacancies Keele University employees wishing to apply should login to Employee Self Service and click on the 'View current vacancies' link. Closing date for applications: 17th June 2020

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The Canadian Computational Neuroscience Spotlight to take place virtually on June 15 and 16
by Scott Rich 02 Jun '20

02 Jun '20

We are happy to announce the upcoming Canadian Computational Neuroscience Spotlight (CCNS) will take place virtually on June 15 and 16. This free meeting will be hosted using the Crowdcast platform, which has been successfully used for numerous virtual conferences over the past weeks and has a multitude of tools to facilitate the interactivity we often associate with traditional conferences. Registration is now open at https://www.crowdcast.io/e/CCNS/register <https://www.crowdcast.io/e/CCNS/register>. The keynote speakers for this event are Dr. Nancy Kopell (Boston University), Dr. Dimitris Pinotsis (City-University of London), Dr. Cameron McIntyre (Case Western University), and Dr. Philip Corlett (Yale University). The entire schedule, including other confirmed speakers, is available at https://www.crowdcast.io/e/CCNS/register <https://www.crowdcast.io/e/CCNS/register>. Our primary goal is for this to be a “trainee focused” meeting, considering it is likely this “next generation” of computational neuroscientists who may be most affected by the recent cancellation and postponement of many traditional physical conferences. Our themed sessions will begin with a “tutorial” talk, providing an introduction to an important topic or tool to be discussed in the session, in order to make the meeting more accessible to trainees at any level. We also will be hosting a panel “Q&A” session each day where trainees will be invited to ask questions of the organizers and speakers about the day’s presentations as well as more general topics. We note that while the meeting has been deemed a “Canadian” spotlight, it is intended for a global audience and includes a similarly global range of speakers. The Canadian focus was developed given that specific conferences in our country scheduled for this summer have been cancelled or postponed, as well as the desire for us to advertise the growing computational neuroscience community across Canada. Please feel free to advertise this meeting in any avenues you deem appropriate, including institutional listservs, lab communication, and social media. We look forward to seeing you at CCNS! Sincerely, Scott Rich, Ph.D. Postdoctoral Research Fellow, Krembil Research Institute. Andreea Diaconescu, Ph.D. Independent Scientist, Krembil Center for Neuroinformatics at CAMH. John Griffiths, Ph.D. Independent Scientist, Krembil Center for Neuroinformatics at CAMH. Milad Lankarany, Ph.D. Scientist, Krembil Research Institute.

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[jobs] 5 PHD POSITIONS IN COGNITIVE ROBOTICS, INTERACTION AND REHABILITATIONS TECHNOLOGIES AT IIT IN COLLABORATION WITH UNIVERSITÀ DI GENOVA - [ PhD ]
by Francesco Rea 02 Jun '20

02 Jun '20

In the spirit of the doctoral School on Bioengineering and Robotics the PhD Program for the curriculum "Cognitive Robotics, Interaction and Rehabilitation Technologies" provides interdisciplinary training at the interface between technology and life-sciences. The general objective of the program is to form scientists and research technologists capable of working in multidisciplinary teams on projects where human factors play a crucial role in technological development and design. The 5 fellowships offered this year by the Istituto Italiano di Tecnologia as part of this curriculum will be assigned to the best applicants to one of the six themes offered within the curriculum, that can be found at the following address under the "Cognitive Robotics Interaction Rehabilitation technologies" Research themes: https://www.iit.it/phd-school/phd-school-genoa Here you can find the direct link to the list of themes in: List of Themes (PDF): https://www.iit.it/phd-school-docs/phd-2020/722-cognitive-robotics-interact… The deadline for the application is at 12:00 (Italian time) of the 15th June 2020 The interested applicants can find more details on the application and unofficial tip & tricks page to the application process: https://www.iit.it/phd-school/phd-school-admission-guide All IIT units involved in this curriculum are located in the "Erzelli" site of the Italian Institute of Technology and share research facilities including, besides two iCub humanoid Robots, a fully equipped motion capture room with simultaneous electromyography recording and force-platforms, a Transcranial Magnetic Stimulation Lab, an Electrophysiology Lab for EEG recording and meeting rooms. The ideal candidates are students with a higher level university degree willing to invest extra time and effort in blending into a multidisciplinary team composed of neuroscientists, engineers, psychologists, physicists working together to investigate brain functions and realize intelligent machines, rehabilitation protocols and advanced prosthesis. Interested applicants are encouraged to contact the perspective tutors for clarifications before submitting their application. International applications are encouraged and will receive logistic support with visa issues and relocation. Within this curriculum, RBCS Robotics, Brain and Cognitive Sciences department sponsors: *) Autonomous learning in human-robot interaction: towards transparent robot symbiosis in skill acquisition *) The role of social signals in human-robot interaction in group *) Cortical networks for affective communication in human robot interaction *) Altered reality for rehabilitation and training of low-vision individuals

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PhD opportunity - Insect Intelligence @ Edinburgh
by Barbara Webb 02 Jun '20

02 Jun '20

The Insect Robotics group led by Prof. Barbara Webb, in the School of Informatics at the University of Edinburgh, has two funded positions available for PhD candidates, to start no later than January 2021. The topic of research will be the neural mechanisms of navigation in insects, building on our recent work modelling the central complex and the mushroom body circuits. Insects have relatively small brains but exhibit substantial intelligence and flexibility in their ability to navigate complex environments, providing an opportunity to understand problems of learning, generalisation, cue integration etc. at the level of single neurons and their connectivity. The primary project aim will be to build detailed computational models, working closely with anatomical and physiological data from our project partners, and to explore the behavioural consequences in simulated and robot agents. There will also be the opportunity to do behavioural experiments on relevant model species such as ants and dung beetles, to complement the modelling results. Students will be fully supported for 3.5 years with a standard stipend, all fees covered, and an allowance for travel and research costs. Interested candidates should in the first instance contact Barbara Webb <B.Webb(a)ed.ac.uk>. Further information about the research degrees in Informatics at Edinburgh and the formal application process can be found here: https://www.ed.ac.uk/informatics/postgraduate -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.

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Two PhD positions in computational modeling of brain areas and neurorobotics
by Jesús Garrido 01 Jun '20

01 Jun '20

The *Applied Computational Neuroscience (ACN) research group* ( https://acn.ugr.es) headed by Prof. Eduardo Ros at the University of Granada (UGR) is looking for talented Master or PhD students interested in working in the field of computational neuroscience and neurorobotics, specifically addressing questions of motor learning and adaptation. The perfect candidate shall possess a strong mathematical, computational or robotic engineering background (or equivalent), with great interest in biological and neural systems. Demonstrated programming skills are mandatory. *Requirements:* - Applicants should have a strong quantitative background (physics, engineering, computer science, applied mathematics), and a keen interest in reverse-engineering the brain. - Demonstrated programming skills (Matlab, C/C++, Python) are required. - Knowledge on computational neuroscience software (BRIAN, NEURON, NEST,…etc ) are a plus although not mandatory. - Robotics control middleware (ROS) is highly valuable. - Robotics (ROS) and programming languages (Matlab, C/C++, Python) are highly valuable. - Proficiency in oral and written English is required. - Knowledge of Spanish is not mandatory. Successful candidates are expected to work in an interdisciplinary environment with collaborations within EU projects. *Full Description of the Job Offer* can be found at: http://sl.ugr.es/hbpcontract *How to apply* Candidates should send a single pdf file containing a motivation letter, a full CV, and names and contact information of at least two referees, to Niceto Luque (nluque(a)ugr.es) and Jesús Garrido (jesusgarrido(a)ugr.es) Short listed candidates will be contacted for an interview (either face-to-face or via videoconference).

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Postdoctoral position in the Neuromodulation and Neuroprosthetics team, led by Dr. Fabien Wagner, at the Institute of Neurodegenerative Diseases, University of Bordeaux, France
by Fabien Wagner 01 Jun '20

01 Jun '20

Our team develops new neuromodulation paradigms and neuroprosthetic systems for repairing or replacing circuit-level functions that get disrupted after neurological disorders or injury. Our research combines techniques from Neuroscience and Neuroengineering , in particular in vivo electrophysiology, signal processing, machine learning and control engineering. We are specifically interested in expanding neuroprosthetic systems from motor to cognitive disorders. In particular, we aim at developing a large-scale brain network neuroprosthesis to restore memory after brain injury or neurodegenerative diseases such as Alzheimer’s disease. To strengthen our team, we are looking to hire a motivated postdoctoral researcher, who will be expected to work on multielectrode recordings and electrical stimulation of large-scale memory networks in non-human primates performing cognitive tasks. The ideal candidate should have expertise in non-human primate electrophysiology, neurostimulation, memory disorders, brain-machine interfaces, or neuroprosthetics. This highly interdisciplinary project requires both experimental and analytical skills, and will be conducted in collaboration with other team members. The position is currently funded for a duration of 3 years. Interested applicants should send their CV to the principal investigator at : [ mailto:fabien.wagner@u-bordeaux.fr | fabien.wagner(a)u-bordeaux.fr ] . Keywords : neuromodulation, neuroprosthetics, neuroengineering, brain stimulation, brain-machine interfaces, memory, cognition. --- Fabien Wagner, Ph.D. Team leader: Neuromodulation and Neuroprosthetics Institut des Maladies Neurodégénératives - CNRS UMR 5293 Université de Bordeaux Centre Broca Nouvelle-Aquitaine - 3ème étage 146 rue Léo Saignat - CS 61292 - Case 28 33076 Bordeaux cedex [ http://www.imn-bordeaux.org/en/teams/neuromodulation-and-neuroprosthetics/ | www.imn-bordeaux.org/en/teams/neuromodulation-and-neuroprosthetics/ ] [ http://www.bordeaux-neurocampus.fr/en/staff/fabien-wagner/ | www.bordeaux-neurocampus.fr/en/staff/fabien-wagner/ ]

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PhD position at Rehab Technologies Lab (Italian Institute of Technology)
by Marianna Semprini 29 May '20

29 May '20

We seek a highly motivate PhD student for working at the Rehab Technologies Lab at IIT. Rehab Technologies is an innovation lab aimed at translating robotic technologies into hi-tech medical products for people with disabilities, including also neural interfaces and personalized neuroengineering solutions for promoting neuroplasticity, with the goal of replacing and/or retraining motor functionalities. We are also interested in monitoring the neural correlates of the rehabilitation treatment, by means of measures based on network connectivity extracted with hdEEG. The PhD project will mainly focus on this activity and will thus include experiments with patients and strong collaboration and interaction with our clinical partners. To this end, the candidate will benefit from a lively network of collaborations with hospitals and research institutions in Italy and abroad. The ideal candidate should: hold a degree in electronic/biomedical engineering or related disciplines, have proficient programming skills (Matlab/Simulink, C and/or Python), be a highly motivated and creative individual who wants to work in a dynamic, multi-disciplinary research environment. Former lab experience and previous technical and scientific results will be highly considered. Applications will be collected through the UNIGE portal https://www.iit.it/careers/openings/opening/1215-1-phd-position-in-bioengin…. Deadline for application is June 15th. Please feel free to contact us for informal enquire. Contacts: michela.chiappalone(a)iit.it<mailto:michela.chiappalone@iit.it>; marianna.semprini(a)iit.it<mailto:marianna.semprini@iit.it> References: * Iandolo R., Semprini M., Buccelli S., Barban F.iit, Zhao M., Samogin J., Bonassi G., Avanzino L., Mantini D., Chiappalone M. (2020). Small-World Propensity Reveals the Frequency Specificity of Resting State Networks. IEEE Open Journal of Engineering in Medicine and Biology. * Semprini M., Laffranchi M., Sanguineti V., Avanzino L., De Icco R., De Michieli L., & Chiappalone M. (2018). Technological approaches for neurorehabilitation: from robotic devices to brain stimulation and beyond. Frontiers in Neurology, 9, 212.

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Post doc position at UCL in human motion sequencing to investigate threat-related behaviour (PI Dominik R Bach)
by Dominik R. Bach 28 May '20

28 May '20

We are looking for a for a Research Fellow in human motion sequencing, for an ERC-funded research project "Action selection under threat - the complex control of human defence" led by Dr Dominik Bach (bachlab.org) The overarching goal of the project is to understand the cognitive-computational control of human motor behaviour under acute, immediate threat. We investigate this in an immersive virtual reality (VR) environment, in which people can move to avoid a large number of different threats. As part of this project, the candidate will conduct full-body motion capture recordings, recover kinematics and dynamics, and structure the ensuing trajectories using hierarchical statistical models incorporating movement mechanics. We want to find out how motor primitives and their sequences are shaped by threat features and by the cognitive mechanisms that they engage. For more background, see references below. The post is based in London UK, at the Max Planck UCL Centre for Computational Psychiatry and Ageing Research (www.mps-ucl-centre.mpg.de <www.mps-ucl-centre.mpg.de/>), which is part of the Wellcome Centre for Human Neuroimaging (fil.ion.ucl.ac.uk) at UCL Queen Square Institute of Neurology, a world-class research environment. Applicants should have (or be close to obtaining) a PhD in machine-learning, robotics, computer science, motor science, biomechanics, computational neuroscience, or a related area, by the agreed start date of the position. Experience with motion capture, inverse kinematics and dynamics (in humans or robots), movement trajectory analysis and structuring are essential. Strong background in contemporary machine-learning and applied statistics is essential, as are solid mathematical skills and good general IT and software development knowledge. Familiarity with virtual reality and/or human/animal defensive behaviour would be desirable. The post is funded from Autumn 2020 for 3 years in the first instance. Starting salary on the UCL salary scale, £35,328 - £42,701 per annum, inclusive of London Allowance, superannuable. Closing date is 24. June 2020. You should apply for this post through UCL's online recruitment system – bit.ly/2LYRH64. Shortlisted candidates will be interviewed remotely in early-mid July. Applicants may contact Dr Dominik Bach directly (email: d.bach(a)ucl.ac.uk) for further information. References: Bach & Dayan (2017) Nature Reviews Neurosciences <http://bachlab.org/wp-content/uploads/2018/03/Bach-Dayan-2017-NRN-Algorithm…> Korn & Bach (2019) Nature Human Behaviour <https://doi.org/10.1038/s41562-019-0603-9> Please circulate - apologies for cross-posting. -- ----------------------- Dominik R Bach MBBS PhD Principal Research Fellow MPCUCL & WCHN, University College London http://bachlab.org | @bachlab_cog

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Postdoc position available - computational modeling and real-time fMRI neurofeedback of language
by Narly Golestani 28 May '20

28 May '20

With the launch of a new ‘NCCR Evolving Language’ (http://www.snf.ch/SiteCollectionDocuments/nfs/Faktenblatt_NCCR_evolvinglang…) which involves nearly 40 different research groups from a large variety of disciplines across Switzerland, we seek to fill a Postdoc position for a four-year project starting in September 2020, or at the selected candidate’s earliest convenience. Our goal is to make progress in understanding the importance of prosody in language processing. To this end, we plan to carry out a set of studies involving both computational modeling of fMRI data and real-time fMRI neurofeedback to understand the mechanisms whereby prosody and rhythm support linguistic processing per se. The computational modeling work will be an extension of our recent work on the neural encoding of acoustic information in speech sounds (https://www.ncbi.nlm.nih.gov/pubmed/31285622) The research will be done in the group of Narly Golestani (www.brainandlanguagelab.org<http://www.brainandlanguagelab.org>) in Geneva, in collaboration with researchers in Switzerland and abroad (Elia Formisano in Maastricht, and Frank Scharnowski in Vienna). Applicants should hold a degree in Biomedical Engineering, Computational Neuroscience, or a related field, and should have solid experience in human brain imaging, and ideally also in computational modelling (i.e. encoding / decoding) of fMRI data, real-time fMRI based neurofeedback, machine learning, statistics and programming. The NCCR places great emphasis on gender diversity and we particularly encourage women to apply. To apply, please send a cover letter, CV, names and contact information of 2-3 references as well as any other relevant documents to Narly.Golestani(a)unige.ch<mailto:Narly.Golestani@unige.ch>. Feel free to contact me should you have any questions. Deadline for application: June 20th 2020 ----------------------------------------------------------------------------------------------------------------------------------------------------------------- Brain and Language Lab Prof. Narly GOLESTANI Department of Psychology Campus Biotech 9 Chemin des Mines, 1202 Genève +41 22 379 53 52 <https://outlook.unige.ch/owa/redir.aspx?SURL=5WTo-p-J-W9FrDydU-0WU4PdMytUGs…>http://www.brainandlanguagelab.org https://twitter.com/brain_lang_lab ----------------------------------------------------------------------------------------------------------------------------------------------------------------- <https://outlook.unige.ch/owa/redir.aspx?SURL=5WTo-p-J-W9FrDydU-0WU4PdMytUGs…>

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ICMNS 2020 - Digital: The 6th International Conference on Mathematical Neuroscience, July 6-7
by Tilo Schwalger 27 May '20

27 May '20

We are delighted to announce the 6th International Conference on Mathematical Neuroscience (ICMNS 2020). Owing to the Coronavirus outbreak, the 6th edition will take place in a virtual format via Zoom on July 6–7, 2020, between 14:00–20:00 (GMT+2). More details are given on the conference website, which will be continuously updated: https://www.danieleavitabile.com/icmns2020digital/ ICMNS is an interdisciplinary conference series, bringing together theoretical neuroscientists and mathematicians. The conferences are aimed at scientists interested in using or developing mathematical techniques for neuroscience problems. This year a broad set of topics in mathematical neuroscience will be covered in eight sessions: (a) Cellular and subcellular dynamics (b) Dynamics of structured neural networks (c) Inferring models from data (d) Mean-field methods in neuroscience (e) Neural fields and spatio-temporal dynamics (f) Neural coding (g) Numerical methods (h) Mathematical theory of deep learning In addition, the conference features a virtual poster session and a special ICMNS Poster Prize. We encourage poster submissions by researchers from all areas of mathematical neuroscience and at all career stages. The submission deadline is the 21st of June at 23:59 (GMT+2). Please keep yourself updated on the webpage. We hope to see you online at ICMNS2020! All the best, Daniele Avitabile, Tatiana Engel, Tilo Schwalger, Wilhelm Stannat -- Tilo Schwalger, PhD Assistant Professor Bernstein Center for Computational Neuroscience, Berlin Philippstr. 13, Haus 6, 10115 Berlin Room: 202, phone: 0049(0)302093 6788 Technische Universität Berlin Institute of Mathematics Straße des 17. Juni 136, 10623 Berlin Room: 726, phone: +49 (0)30 314-22698

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Assistant Professor / Postdoc position in computational neuroscience and/or developmental robotics at the University of Tokyo
by Yukie Nagai 27 May '20

27 May '20

Dear colleagues, The International Research Center for Neurointelligence (IRCN) at the University of Tokyo is looking for highly motivated full-time Assistant Professor / Postdoc researchers in the field of computational neuroscience and/or developmental robotics. The selected candidates will join Cognitive Developmental Robotics Laboratory and have the opportunity to pursue interdisciplinary research integrating computer science, neuroscience, cognitive science, psychology, robotics, etc. If you are interested in being considered, please send the required documents to yukie(a)ircn.jp. Assistant Professor / Postdoc Researcher at IRCN, the University of Tokyo https://ircn.jp/en/careers/Postdoctoral-Fellow-Project-Researcher-Nagai-Lab… Cognitive Developmental Robotics Laboratory (Nagai Lab), the University of Tokyo http://developmental-robotics.jp/en/ --------------------------------------------------------------------------------- 1. Job title: Project Assistant Professor / Project Researcher (Postdoctoral Fellow) 2. Starting Date: Negotiable 3. Term: The first contract will be ended on March 31, 2021. The contract is renewable on a fiscal year basis (from April 1 to March 31; every year) according to research budget, research activity, and research achievements. Contract duration is until March 31, 2023. 4. Place of Work International Research Center for Neurointelligence The University of Tokyo, Institutes for Advanced Study 7-3-1 Hongo Bunkyo-ku Tokyo, 113-0033 JAPAN 5. Qualifications (Required) - Ph.D. in Engineering, Ph.D. in Computer Science or equivalent in a related field - Good communication skill in English (Preferred) - Experiences in computational neuroscience, neural network, machine learning, and/or developmental robotics will be preferred. 6. Compensation & Benefits - Salary: To be determined in accordance with the University of Tokyo Regulations - Commuter allowance: JPY55,000 per month at maximum - Social Insurance: Eligible for MEXT Mutual Aid Association membership, employees’ pension, employment insurance, and workers’ accident compensation insurance. - Vacation: Annual paid vacation, Sick leave (paid), Special vacation (paid) 7. Working Hours Discretionary labor system, based on 7 hours, 45 minutes per day, or 38 hours 45 minutes per week 8. Holidays Saturdays and Sundays; Statutory public holidays of Japan; Year-end and New Year holidays (December 29 through January 3); Summer holidays 9. Applications and Selection Process - Applications deadline: When the position is filled - Application documents: (a) Cover letter in English (b) Curriculum vita in English (c) Publication list (d) Name and contact address for two references, one of which should be a previous employer - Submission: Interested applicants should send application materials to: yukie(a)ircn.jp - Selection Process: All applications will be screened, and only those qualified will be scheduled for an interview (on-site or via video). --------------------------------------------------------------------------------- — Yukie Nagai, Ph.D. Project Professor, The University of Tokyo nagai.yukie(a)mail.u-tokyo.ac.jp | http://developmental-robotics.jp CREST Cognitive Mirroring: http://cognitive-mirroring.org

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NEST Conference 2020 — Submission deadline 1 June 2020
by Hans Ekkehard Plesser 26 May '20

26 May '20

Dear all, Just a little reminder that the submission deadline for the (virtual) NEST Conference 2020 is this Monday, June 1st. We are looking forward to your contributions. The NEST Conference provides an opportunity for the NEST Community to meet, exchange success stories, swap advice, learn about current developments in and around NEST spiking network simulation and its application. This year's conference will take place as a virtual conference on Monday/Tuesday 29/30 June 2020. We are inviting contributions to the conference, including plenary talks, "posters" and breakout sessions on specific topics. Important dates 01 June 2020 — Deadline for submission of contributions 08 June 2020 — Notification of acceptance 10 June 2020 — Deadline for NEST Initiative Membership applications (registration is free for members in 2020) 22 June 2020 — Registration deadline 29 June 2020 — NEST Conference 2020 starts For more information on how to submit your contribution, register and participate, please visit the conference website https://nest-simulator.org/conference We are looking forward to seeing you all in June! Hans Ekkehard Plesser, Susanne Kunkel, Dennis Terhorst, Anne Elfgen & many more -- Prof. Dr. Hans Ekkehard Plesser Head, Data Science Section Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no Home http://arken.nmbu.no/~plesser

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Faculty position at CHAIN: Assistant Professor or Lecturer
by Hideaki Shimazaki 24 May '20

24 May '20

Dear colleagues, Our newly established Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN) at Hokkaido University in Japan invites applications for a faculty position at the Assistant Professor or Lecturer level. The full description and details are attached below. See also: https://jrecin.jst.go.jp/seek/SeekJorDetail?fn=3&ln=1&id=D120050453&ln_jor=1 https://www.chain.hokudai.ac.jp/?lang=en The deadline for applications is 8 June 2020 (JST). All the best, Hideaki --- Hideaki Shimazaki, Ph.D https://www.neuralengine.org Position Open: Assistant Professor or Specially Appointed Lecturer, Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN), Hokkaido University Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN), Hokkaido University, in Hokkaido, Japan invites applications for a 3.5 year research and teaching position with an anticipated start date of September 1st, 2020. The successful applicant will be appointed as a faculty member at the rank of Specially Appointed Assistant Professor or Lecturer in CHAIN. Women and members of other underrepresented groups are particularly encouraged to apply. CHAIN is a research and education center for interdisciplinary studies in the humanities, social sciences, neuroscience, and artificial intelligence. It aims to open up new directions of research into the nature of human existence by fostering interaction and collaboration between humanities and the social sciences, including philosophy, ethics, psychology (cognitive and social), law, and economics, and the natural sciences, such as neuroscience, AI, and cognitive science. In particular, it focuses on connecting philosophical ideas with methods and insights of mathematical and empirical sciences. A new interdisciplinary graduate program of CHAIN starts in July 2020. Qualifications The ideal applicant will have an independent research project that will strengthen and complement existing interdisciplinary research in CHAIN. They are expected to demonstrate the following qualities and characteristics: 1. A PhD by the time of the appointment in one (or more) of the following area(s): philosophy, ethics, psychology, cognitive science, neuroscience, AI, information science, or robotics. 1. Outstanding publication records and/or demonstrable potential to publish in highly esteemed publication outlets. 1. Strong motivation to fulfill research, teaching, and administrative duties as a faculty member in CHAIN. 1. Enthusiasm and competence for delivering postgraduate and undergraduate courses on topics pertinent to CHAIN’s research and education goals. 1. A demonstrated ability and strong interest to develop and engage in interdisciplinary research projects in collaboration with existing members of the institution. Application materials Submit the following materials, compiled in a single ZIP file, via email at jobs [at]chain.hokudai.ac.jp to complete your application: 1. Curriculum Vitae* 2. Summary of past research accomplishments (1-2 pages) 3. Three most important publications relevant to this position. 4. Brief statement of research and teaching interests (1-2 pages) 5. Two references (Names and contact details) Use common fonts such as Times New Roman in black and size 12 points. Submit each publication in a separate PDF file. Compile all the rest (1, 2, 4, and 5) in a single PDF file. This makes four PDF files in total, which must then be compiled in a single ZIP file. Submission is due Monday, 8 June, 2020 (JST). The subject line of the email must read “Application (Lecturer/Assistant Professor).” You will receive a confirmation email shortly after making a submission. Please contact us immediately if you did not receive one within 3 business days. Personal information obtained through these materials will only be used within this selection process. *Applicants who have been employed by Hokkaido University after April 1, 2014 (in any position, including Part-time Lecturer, Teaching Assistant, Teaching Fellow, Research Assistant and Short-term Support Assistant, etc.) should provide full details of their employment history in the CV. Appointment terms This is a full-time research and teaching position with an anticipated start date of September 1st, 2020. The salary will be paid under the annual-salary scheme and the discretionary labor system. The annual salary is determined in accordance with the internal regulations of Hokkaido University. Upon employment, one will be enrolled in the Ministry of Education, Culture, Sports, Science and Technology Mutual Aid Association, Employees Pension, Workers’ Accident Compensation Insurance and Employment Insurance. A one month probationary period applies. Questions about the position should be addressed to the chair of the search committee, Shigeru Taguchi (inquiry[at]chain.hokudai.ac.jp). Further information Website: www.chain.hokudai.ac.jp/?lang=en Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN) Hokkaido University Kita 12 Nishi 7, Kita-ku, Sapporo Hokkaido 060-0812 Japan Application submission: jobs [at] chain.hokudai.ac.jp Inquiries: : inquiry [at] chain.hokudai.ac.jp

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Publication of the NeurIPS2019 Reproducibility Challenge reports
by Nicolas P. Rougier 22 May '20

22 May '20

Dear all, The accepted reports for the NeurIPS2019 Reproducibility challenge have just been published at https://rescience.github.io/read (volume 6, issue 2). All articles are open access with open code, data and reviews. Nicolas Rougier ReScience C Editor-in-chief

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Community review of two new standards now open
by Helena Ledmyr 22 May '20

22 May '20

INCF has two new community standards up for public review, and we are now soliciting input from the user community. The standards are the Neuroscience Information Exchange (NIX) and the Neuroimaging Data Model (NIDM)-Results. More information is available here: https://www.incf.org/comment-on-these-sbps *The mission of the INCF is to develop, evaluate, and endorse standards and best practices that embrace the principles of Open, FAIR, and Citable neuroscience. INCF also provides training on how standards and best practices facilitate reproducibility and enables the publishing of the entirety of research output, including data and code.* All the best Helena ----------------------------- Helena Ledmyr, PhD *Director* *Development and Communications* International Neuroinformatics Coordinating Facility Secretariat Karolinska Institutet. Nobels väg 15A, SE-171 77 Stockholm. Sweden Email: helena.ledmyr(a)incf.org Phone: +46 8 524 870 35 incf.org neuroinformatics.incf.org

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Call for papers: Neuroinformatics special issue "Building the NeuroCommons"
by Helena Ledmyr 22 May '20

22 May '20

Neuroinformatics is currently soliciting submissions for a special issue called "Building the NeuroCommons - research and commentary on how neuroscience is becoming open and FAIR". Submissions due *July 31 2020*. As neuroscience increasingly defines and adopts FAIR, the act of publishing in neuroscience will not only serve to communicate new research but drive the population of a robust, more data- and resource-driven ecosystem - the NeuroCommons - on which to build further findings. This special, open-access, issue of Neuroinformatics is dedicated to building the NeuroCommons and will include articles that embody the principles of open and FAIR neuroscience: - FAIRification of neuroscience data, tools and other research objects: What does it take to move neuroscience closer to the ideal of FAIR? - Using public data to drive discovery science - Research infrastructure for neuroscience and how it supports open and FAIR neuroscience - Standards-based neuroscience. When and where have standards been effective? What have we learned about creating standards and gaining adoption? Where are they lacking? - Perspectives and commentary on the concept of the NeuroCommons, e.g., what will it take for neuroscience to become a data-driven discipline based on pools of open research data? What are challenges and opportunities? Where have there been successes? More information and submission at https://www.springer.com/journal/12021/updates/17978796 All the best Helena ----------------------------- Helena Ledmyr, PhD *Director* *Development and Communications* International Neuroinformatics Coordinating Facility Secretariat Karolinska Institutet. Nobels väg 15A, SE-171 77 Stockholm. Sweden Email: helena.ledmyr(a)incf.org Phone: +46 8 524 870 35 incf.org neuroinformatics.incf.org

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Imperial College MRes in Neurotechnology
by Kozlov, Andriy 21 May '20

21 May '20

Imperial College MRes in Neurotechnology Neurotechnology is the use of insights and tools from mathematics, physics, chemistry, biology and engineering to investigate neural function and treat dysfunction. Brain-related illnesses affect more than two billion people worldwide, and the numbers are growing. Reducing this burden is a major challenge for society. The MRes Neurotechnology<http://www.imperial.ac.uk/bioengineering/study/postgraduate-research/mres-n…> is a one-year full-time programme which will provide you with technical knowledge, expertise and transferable skills in this exciting area. Our MRes will prepare you for an innovative research career at the interface between neuroscience and engineering, in academia, industry, or elsewhere. The programme comprises lectures, practical work and workshops in the first term, followed by full-time work on a research project<http://www.imperial.ac.uk/bioengineering/study/postgraduate-research/mres-n…>. In addition, you will attend regular seminars and a journal club throughout the year. Your research project will normally be supervised by a multidisciplinary team of at least two Imperial College London<https://www.imperial.ac.uk> supervisors who will bring technical and neuroscience expertise to the project. Careers The MRes Neurotechnology provides unique training at the interface between neuroscience and engineering, enhancing your skills in research, analysis and scientific presentation and developing your ability to work in a multidisciplinary team. Our programme provides a solid foundation in research for those continuing with a neurotechnology career, whether through a PhD or working in industry. How to apply Please visit our webpage<http://www.imperial.ac.uk/bioengineering/study/postgraduate-research/mres-n…> for full details of the course and how to apply, including entry requirements and projects available for 2020 entry<http://www.imperial.ac.uk/bioengineering/study/postgraduate-research/mres-n…>. The deadline for applications is 15 June, but applications are considered on a rolling basis, so we encourage you to apply now. ******************** Thank you. Best wishes, Andrei Kozlov (Director of the MRes in Neurotechnology)

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DEPSCoR funding opportunity for tenured/tenure-track faculty in select US states/territories
by GREENWALD, HAL S DR-04 USAF AFMC AFOSR/RTA 20 May '20

20 May '20

The Defense Established Program to Stimulate Competitive Research (DEPSCoR) is a capacity building program that is designed to strengthen the research infrastructure at institutions of higher education in underutilized states/territories. Eligible applicants are full-time tenured or tenure-track faculty members at institutions of higher education in the following US states/territories: Alabama, Alaska, Arizona, Arkansas, Connecticut, Delaware, District of Columbia, Guam, Hawaii, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Mexico, North Dakota, Oklahoma, Oregon, Puerto Rico, Rhode Island, South Carolina, South Dakota, Tennessee, U.S. Virgin Islands, Vermont, West Virginia, Wisconsin, and Wyoming. Applicants must never have served as the PI on a prior DoD-funded award. Applicants must select a co-PI/collaborator who is a tenured or tenure-track faculty member at an institution of higher education in a DEPSCoR-eligible state/territory and has served as the PI on a DoD-funded research award active between 1 October 2013 and 30 September 2020. Awarded grants may be for up to $200,000 per year for three years. Topic areas: Air Force Office of Scientific Research: 1. Cognitive and Computational Neuroscience 2. Space Science 3. Agile Science of Test and Evaluation 4. Materials with Extreme Properties Army Research Office: 5. Propulsion and Energetics 6. Computational Architectures and Visualization 7. Optoelectronics 8. Probability and Statistics 9. Molecular Structure and Dynamics 10. Social and Behavioral Science 11. Biotronics Office of Naval Research: 12. Aerospace Structures and Materials 13. Ocean Acoustics 14. Machine Learning, Reasoning, and Intelligence 15. Power Electronics & Electromagnetism, Adaptive & Machinery Controls and Advanced Machinery Systems For complete details, please see the funding opportunity announcement at https://www.grants.gov/web/grants/view-opportunity.html?oppId=326765. White papers are due by 21 September 2020. Hal S. Greenwald, Ph.D. Program Officer, Cognitive & Computational Neuroscience Air Force Office of Scientific Research (AFOSR/RTA) 875 N. Randolph St. Arlington, VA 22203-1768 (703) 588-8441

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PhD position Deep Learning for MRI-based addiction research
by Fabian Eitel 20 May '20

20 May '20

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PostDoc in Reinforcement Learning for Intensive Care Treatment (including Covid-19) @ Imperial College London
by Faisal, Aldo A 20 May '20

20 May '20

Dear All, We are looking for a Post-Doctoral research fellow to join our machine learning effort to establish the computational foundations for an “AI clinician” (Komorowksi et Faisal, 2018, Nature Medicine; Li et Faisal, 2020, ICLR AI4Health). While a “fully autonomous doctor” is far more ambitious (and perhaps undesirable) than self-driving cars (Topol, 2019, Nature Medicine), our goal is to link our work in the established foundations of clinical decision recommendation systems and evaluate our developments in a meaningful clinical setting. This vision in turn requires the development of novel RL techniques, which are at the heart of this fellowship, such as causal inference in RL and explainable RL (XRL). We have previously shown that RL and Bayesian Optimization can be applied for learning optimal interventions in closed loop (Bohte et al, 2013, Lorenz et al, 2016). We work on methods allowing us to train RL agents interactively (off-policy policy estimation) on historical data of medical interventions (“actions”) and patient responses to them (“state”). We want to build on our groundwork drawing on causal inference, deep- and kernel-based machine learning (Liu et al, 2018, NeurIPS; Parbhoo et al, 2018, PLOS1; Peng et al, 2018, AMIA) and explainable RL (Shafti et al, IROS, 2019) for the emerging domain of RL for medical interventions. Crucially, we believe that Machine Learning for medical intervention may have a larger impact on health than diagnostics, as treatment is where medicine really starts helping people. Crucially, we are working on both the theory and application for RL in healthcare and have as a team already the necessary regulatory approvals for clinical evaluations in our university hospitals are in place and already recruited clinical staff and hospital IT teams. Moreover, as our domain application is the optimal treatment of patient intensive care units, the PostDoc will have the opportunity to join the fight against Covid-19 to save lives by better understanding. Our lab is leading the data science effort for the UK national service evaluation in critical care (https://www.imperial.ac.uk/artificial-intelligence/research/covid/covid-icu/) and is thus working on data from ICUs across an entire country to identify optimal treatment policies. Advert here: https://www.imperial.ac.uk/jobs/description/ENG01259/research-associate https://www.jobs.ac.uk/job/BZP190/research-associate Applications can be received after the advertised deadline (which will be also extended due to Covid-19). Please do reach out to me to find out more. kind regards Aldo -- Aldo Faisal Director, Centre in AI for Healthcare – https://ai4health.io Reader in Neurotechnology -- https://FaisalLab.org Data Science Institute, Dept. of Computing & Dept. of Bioengineering Imperial College London

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PhD scholarship on spiking network computational models at Barcelona
by Xavier Otazu 18 May '20

18 May '20

The Neurocomputation and Biological Vision Team (NeuroBiT) (<http://www.cvc.uab.es/neurobit> ) offer a PhD scholarship to work in a highly multidisciplinary project which includes computational modelling of primary visual cortex and psychophysical experimentation of colour perception and its relationship to visual migraines. The Research will take place at the Computer Vision Centre <http://www.cvc.uab.es> (http://www.cvc.uab.es) of the Univ. Autònoma de Barcelona, which is consistently ranked among the top Spanish Universities <https://www.uab.cat/web/about-the-uab/the-uab/the-uab-in-the-rankings-13456…> (https://www.uab.cat/web/about-the-uab/the-uab/the-uab-in-the-rankings-13456…) The centre is located in a campus outside the vibrant city of Barcelona and has a strong tradition of multidisciplinary research in computational colour vision with their own psychophysical laboratory, living labs facilities and several computer clusters. The candidate will be part of the NeuroComputation and Biological Vision Team (NeuroBiT <http://www.cvc.uab.es/neurobit/> ), a recently-formed multidisciplinary research group which combines perceptual and computational approaches with visual neuroscience. We offer regular meetings with other PhD students, international contacts and the possibility of internship/cooperation with other experimental/theoretical labs. The successful candidate is likely to obtain several high-impact publications. The student research topic will be one of the following (to discuss with the candidate): 1) The development of recurrent multilayer spiking networks to reproduce the biological architecture of the primary visual cortex and several of its physiological properties, aiming at reproducing the results of psychophysical studies in colour perception and clinical studies on migraines. 2) Use of STDP (Spike Time Dependent Plasticity) for the definition of biologically plausible deep learning computational architectures (i.e. SNN –Spiking Neural Networks-). The duration of the position is 4 years (48 months). We expect the position to start on september/october 2020 (i.e. eventual visa issues should be solved beforehand!). The total annual stipend of the grant is around €15.000 gross, which include the cost of registration fees for the official doctorate program. Conditions: The candidate must * hold a European Higher Education Area (EHEA) qualification of at least 300 ECTS credits or a university-awarded Master degree or equivalent in the natural sciences/engineering at the time of signing the contract. * have experience in programming with Python and/or Matlab (C, C++, Unix environment and computer cluster experience are also valued) * have knowledge of / interest in the human visual system, visual perception and statistics * proficiency in English and Spanish * have excellent skills in analytical thinking, perceptiveness, commitment, self-organization, teamwork, and communication Any previous experience in the subject of computational modelling will also be a bonus. How to apply: Please send your CV and a short statement (500 words) connecting your previous work with the topics of this grant to xotazu(a)cvc.uab.es <mailto:xotazu@cvc.uab.es> and a copy of the official academic transcript (including GPA). We encourage candidates with strong skills in programming who are interested to work in a highly multidisciplinary project and environment (computer science, neuroscience, psychophysics), to apply. Candidates should have a degree in a related subject (Neuroscience, Computer Science, Mathematics, Physics, Biology, etc.).

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PhD position in computational neuroscience and robotics
by Xavier Hinaut 15 May '20

15 May '20

A PhD position is available at the Inria Bordeaux Sud-Ouest center and the Institute of Neurodegenerative Disease in Bordeaux, France. What: PhD position in computational neuroscience and robotics Where: Inria, Bordeaux, France When: October 2020 (3 years duration) Who: Xavier Hinaut & Frédéric Alexandre Application deadline: May 22th (22/05/2020) How to apply: https://jobs.inria.fr/public/classic/en/offres/2020-02637 Title of the PhD topic ================= NewSpeak: Neuro-computational models of language comprehension and production grounded in robots Keywords ================= Recurrent Neural Network (RNN), Reservoir Computing, Developmental Language Learning, Neuro-Robotics, Multimodal Language Grounding, Computational Neuroscience, Reinforcement Learning Candidate profile ================= - Good background in maths and computer science; - A strong interest for neuroscience and the physiological processes underlying learning; - Python programming with experience in scientific libraries Numpy/Scipy (or similar coding language: matlab, etc.); - Experience in machine learning or data mining is a preferred; - Independence and ability to manage a project; - Good English reading/speaking skills. Proposed research ================= We target to embody models into robots that will developmentally ground language. The grounding of semantics should come from the robot experiencing the world through its interactions with humans and the physical world. The goals are (1) to test hypotheses with biologically plausible language learning models with the Nao robot, (2) to extend the current model with unsupervised training and by reinforcement learning, and (3) to propose a new kind of Generative Adversarial Networks (GANs) for developmental language learning conditioned by grounded modalities such as vision. In order to model how a sentence can be processed, word by word (Hinaut & Dominey 2013) or even phoneme by phoneme (Hinaut 2018), the use of recurrent (artificial) neural networks, such as Reservoir Computing, offers interesting advantages. In particular the possibility to compare the dynamics of the model with data from neuroscience experiments (EEG, fMRI, ...). This paradigm allows to learn with few learning examples, and offers negligible runtime for human-robot interactions. The use of linguistic models with robots is not only useful to validate the models in real conditions, it also allows to test other hypotheses, notably on the anchoring of the language or the emergence of symbols. This involves finding out how a learning agent can link and categorise physical stimuli (vision, hearing, proprioception, etc.) to make the correspondence with symbols (Harnard 1990), or even to make these symbols emerge from stimuli coming from sensors (Taniguchi et al. 2016). We aim that a robot could process language from morphemes to sentences, similarly as a child, in order to better model how children acquire language. One aim is to obtain symbolic representations that are a composition of multimodal grounded representations. We will experiment how the newly developed language model will be able to learn to understand utterances by exploring which meanings the morphemes, words, ... can have based on other modalities of the robot (e.g. vision, proprioception). Starting from preliminary results (Juven & Hinaut 2020), we will first consider merging the representations from vision with a pre-trained CNN (Convolutional Neural Network). Then, reinforcement learning experiments will explore how the robot can learn the meaning of sentences: first by doing random actions for any user utterance, and then bootstrap from the user’s feedback. We will use a concrete corpus of sentences based on actions a robot can do (Hinaut & Twiefel 2019). We will implement several variants of language models: (1) extension of the reservoir computing model linked with grounded CNN, (2) adapt such model to the GAN paradigm in order to couple language comprehension and production in a self-learning generative mechanism (thus creating more biologically plausible GANs), (3) explore unsupervised (cross-situational learning) and reinforcement learning with these models. In parallel, we will adapt models features and behaviours to the ones observed in language acquisition experiments in psychology, and neural evidences in neuro-linguistic studies. In particular, we will explore how the models could shed light on language developmental impairments. We will run models in simulated humanoid robots and in a Nao robot. More information ============ More information is available on the application web page: https://jobs.inria.fr/public/classic/en/offres/2020-02637 Questions can be asked by email to Xavier Hinaut (xavier.hinaut(a)inria.fr) Xavier Hinaut Inria Researcher (CR) Mnemosyne team, Inria LaBRI, Université de Bordeaux Institut des Maladies Neurodégénératives +33 5 33 51 48 01 www.xavierhinaut.com

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Postdoc position in the Mainen lab at Champalimaud
by Luca Mazzucato 14 May '20

14 May '20

Systems Neuroscience Postdoctoral Fellow The Champalimaud Foundation, a private, non-profit research institution, is opening a call for a post-doctoral researcher, within the scope of the research project entitled "Neural mechanism of value based decision making of staying or leaving - Deciding when to initiate locomotion to move to the next reward location." This position involves data analysis/modeling of foraging behavior and self-initiated movements in rodents, related to a Systems Neuroscience experiment addressing the following question. When interacting with a complex environment, animals generate naturalistic behavior in the form of action sequences. To analyze and classify such behavior from video recordings is a computationally demanding task, requiring development of specific software pipelines adapted for big data structures using deep learning methods and state space models. This project aims at creating such a pipeline for analyzing videos of mouse behavior previously collected in the Mainen Lab at the Champalimaud Center for the Unknown, Portugal. In the experiment, animals performed certain action sequences, with variable onsets timing, leading to a water reward. Optogenetics photostimulation of inhibitory neurons in secondary motor regions was also performed during selected action sequences. Behavior during this task was recorded with two high speed, high resolution cameras pointing at the animal's face and front limbs. The large size of the datasets generated in this experiment (~1 Tb per animal, for 10 animals) requires an extensive effort to classify behavioral motifs. In the second part of the project, behavioral motifs will be related to large scale recordings of neural activity from Neuropixel probes. The fellow will investigate the relationship between neural activity and behavior using state space models and mechanistic models based on recurrent neural networks. The fellow will integrate a dynamic team of researchers as part of an international collaboration between the Mainen Lab <https://mainenlab.org/> at the Champalimaud Centre for the Unknown and the Mazzucato Lab <https://www.mazzulab.com/> at University of Oregon. National, foreign and stateless candidates can develop the proposed work remotely where team interaction is supported by online platforms (e.g. slack, zoom, etc). *References:* Recanatesi, S. et al., biorxiv (2020). Vertechi, P. et al., Neuron (2020). Murakami, M. et al., Neuron (2017). Murakami, M. et al., Nat. Neuro (2014). Essential qualifications: PhD in Neuroscience, Cognitive Science, Biology, Experimental Psychology, Engineering, Physics, Mathematics, or other areas relevant to neurophysiology and animal behavior; Proficiency in Python and Matlab programming language and familiarity with object oriented programming; Familiarity with Deep Learning software (TensorFlow); Familiarity with data analysis of biological experiments; Ability to work independently and troubleshoot technical issues; Good capacity and value for teamwork and communication skills; Fluency in English. REMUNERATION The monthly remuneration to be attributed is the 33rd level of the single remuneration table (TRU), approved by Portaria nº 1553-C/2008, of December 31st, starting at a base gross salary of 2,128.34 Euros. SELECTION PROCESS Applications will be accepted until June 15th, 2020 or until a qualified candidate is hired. Candidates must submit a single document (maximum 4 pages; paper or PDF file) that contains a motivation letter and the Curriculum Vitae, both written in English. Email applications must be addressed to careers(a)research.fchampalimaud.org and include “CPD2020-LOCODECISION” in the subject line. The selected candidate must submit proof of her/his PhD or Doctoral Degree within 10 days following notification of the preliminary results. More information about Diplomas recognition may be found in the Euraxess portal <http://www.euraxess.pt/portugal/information-assistance/recognition-diplomas> . All candidates who formalize their application incorrectly or who fail to provide the requirements imposed by this tender are excluded from admission. In case of doubt, the panel is entitled to request further documentation to support candidate statements. Notification of Results: The highest scoring candidate will be notified by email or telephone. All other candidates will be notified solely by email. Non-discrimination and equal access policy: The Champalimaud Foundation actively promotes a policy of non-discrimination and equal access, so that no candidate can be privileged, benefited, harmed or deprived of any right, on basis of age, sex, sexual orientation, marital status, family status, economic situation, education, social origin or condition, genetic heritage, reduced working capacity, disability, chronic illness, nationality, race, territory of origin, language, religion, political or ideological convictions, and trade union membership.

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Call for 22 PhD positions in BioRobotics at the BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
by Calogero Maria Oddo 13 May '20

13 May '20

************************************* 22 PhD positions in BIOROBOTICS open! https://www.santannapisa.it/sites/default/files/flyer_phd_biorobotica_2020_…. ************************************* The PhD Program in BioRobotics is a three-year course managed by the BioRobotics Institute (http://sssa.bioroboticsinstitute.it) in the Department of Excellence in Robotics & AI, at Sant’Anna School of Advanced Studies, in Pisa (Italy). The PhD in BioRobotics is one of the largest doctoral schools worldwide in biomedical engineering and robotics, with about 100 PhD students enrolled. All positions are fully funded by Sant'Anna and the Italian Institute of Technology.The number of positions awarded could be expanded with additional fellowships that may be available before the start of the PhD course in October 2020. The students are educated in a stimulating and multidisciplinary environment, both through high-level courses and through demanding, creative and original research work. PhD projects are carried out in very well equipped, state-of-the-art laboratories (in such fields as micro-engineering, biomedical engineering, biomimetic and soft robotics, rehabilitation technologies, surgical robotics and neural engineering, robot companions) and through individual and team work performed under the supervision of a full-time faculty. ADMISSION: Students are admitted to the PhD Program following a successful entrance examination. Eligible applicants must hold a Master of Science (M.Sc.) degree or equivalent. Undergraduate students may also apply if they graduate within Oct. 31, 2020. START: Oct. 1, 2020 CALL details: https://www.santannapisa.it/en/admissions/call-admission-phd-biorobotics-3 APPLY at: www.santannapisa.it/en/education/phd-biorobotics DEADLINE: June 3, 2020 CONTACT: PhDBiorobotics(a)santannapisa.it Best regards, Calogero Oddo, on behalf of the PhD Board -- Calogero M. Oddo PhD BioRobotics, MSc and BSc Electronic Engineering Associate Professor of Bioengineering https://www.santannapisa.it/en/calogero-maria-oddo Vice-Coordinator of the PhD programme in BioRobotics Sant'Anna School of Advanced Studies, Pisa, Italy https://www.santannapisa.it/en/education/phd-biorobotics Head of the Neuro-Robotic Touch Laboratory, Neuro-robotics Area, The BioRobotics Institute Viale Rinaldo Piaggio 34, 56025, Pontedera (PI), Italy Sant'Anna School of Advanced Studies, Pisa, Italy http://www.santannapisa.it/en/neuro-robotic-touch-laboratory Department of Excellence in Robotics & AI Sant'Anna School of Advanced Studies, Pisa, Italy Piazza Martiri della Libertà, 33 - 56127 Pisa, Italy https://www.santannapisa.it/en/robotics-ai IEEE Senior Member, Founding Vice-Chair of the Italian Chapter of the IEEE Sensors Council (2018-20) http://sites.ieee.org/italy-sensors/about-ieee Office: +39050883067; Mobile: +393316992273; email:calogero.oddo@santannapisa.it -- Questa e-mail è stata controllata per individuare virus con Avast antivirus. https://www.avast.com/antivirus

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