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PhD position in Computational Modelling and Machine Learning at IT University of Copenhagen (deadline March 20th)
by Stefan Heinrich 13 Feb '23

13 Feb '23

PhD position at IT University of Copenhagen, Denmark, starting in Summer 2023. Topic: Modelling hierarchical learning of music and speech processing. How does the human brain hierarchically process music or speech? It seems the brain is dynamically adapting to the timescales in the sensation in a way that components of music, such as melodies and low base lines are processed and integrated differently. Furthermore, it seems crucial that the brain is using a statistical learning scheme, thus learning this adaptation by how frequently these components occur. Despite a number of existing neuroimaging studies and scarce attempts to suggest underlying computational principles, research for detailed models is open. We plan modelling the learning of music by studying different computational mechanisms, both, more precise and w.r.t. its functionality close to specific biological neuron models, as well as more coarse, based on general computational principles such as hierarchical network structure, decoding schemes, and distributed activation. The computational research will be conducted side-by-side with a series of empirical EEG studies to verify the validity and further specify the models. The project is part of a cross-departmental initiative between the departments of computer science and digital design aimed at investigating machine-learning-based computational models of the human mind in relation to digital media interaction. Results from this project can enable understanding human information processing better, as well as applying derived computational principles in AI and machine learning approaches of the next generation. Application details: The ideal candidate should have a Masters in Computer Science, Computational Neuroscience, Developmental Psychology, Cognitive Science or related fields, as well as a strong interest in interdisciplinary research, at the intersection of Computational Modelling and Machine Learning. The salary scale will be in accordance with the Ministry of Finance’s agreement with the Danish Confederation of Professional Associations for a full-time position. ITU is a teaching and research-based tertiary institution concerned with information technology (IT) and the opportunities it offers. The University offers an informal working environment, a varied everyday life, and a highly motivated, competent, and 160 diverse international faculty. Copenhagen has a strong educational system, a rich cultural life, universal healthcare, good childcare, and a well-functioning infrastructure. The city is also among the world’s most liveable cities according to the Economist Global Liveability Index. Candidates will work together with Stefan Heinrich (stehe(a)itu.dk) and Paolo Burelli (pabu(a)itu.dk) and are encouraged to get in contact to develop the project details together. Link to apply and further application details: https://candidate.hr-manager.net/ApplicationInit.aspx?cid=119&ProjectId=181… Application deadline: 20 March 2023, at 23:59 CET. -- *************************** Dr. Stefan Heinrich Assistant Professor Computer Science Department IT University of Copenhagen https://stefanheinrich.net/ ***************************

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1ˢᵗ Advanced Scientific Programming in Python - Latin America in Mexico City, Mexico, 26 June – 1 July, 2023
by Jakob Jordan 13 Feb '23

13 Feb '23

ASPP-LatAm: 1st Advanced Scientific Programming in Python - Latin America ========================================================================= a Summer School by the ASPP faculty, the National Autonomous University of Mexico and the Secretarı́a de Educación, Ciencia, Tecnologı́a e Innovación de la Ciudad de México. https://latam.aspp.school Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are devised to be interactive and to give the students enough time to acquire direct hands-on experience with the materials. Students will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project — an entertaining computer game. We use the Python programming language for the entire course. Python works as a simple programming language for beginners, but more importantly, it also works great in scientific simulations and data analysis. We show how clean language design, ease of extensibility, and the great wealth of open source libraries for scientific computing and data visualization are driving Python to become a standard tool for the programming scientist. This school is targeted at Master or PhD students and Post-docs from all areas of science. Competence in Python or in another language such as Java, C/C++, MATLAB, or R is absolutely required. Basic knowledge of Python and of a version control system such as git, subversion, mercurial, or bazaar is assumed. Participants without any prior experience with Python and/or git should work through the proposed introductory material before the course. We are striving hard to get a pool of students which is international and gender-balanced. Date & Location ============= 26 June – 1 July, 2023. Mexico City, Mexico. Application ========= You can apply online: https://latam.aspp.school Application deadline: 23:59 UTC, Sunday March 12, 2023. There will be no deadline extension, so be sure to apply on time. Be sure to read the FAQ before applying: https://latam.aspp.school/wiki/faq Participation is for free, i.e. no fee is charged! Participants however should take care of travel, living, and accommodation expenses by themselves. We are in the process of securing some funds for supporting students with accommodation and living costs. Program ======= • Version control with git and how to contribute to open source projects with GitHub • Best practices in data visualization • Testing and debugging scientific code • Advanced NumPy • Organizing, documenting, and distributing scientific code • Advanced scientific Python: context managers and generators • Writing parallel applications in Python • Profiling and speeding up scientific code with Cython and numba • Programming in teams Tentative Faculty ================= • Aitor Morales-Gregorio, Theoretical Neuroanatomy, Institute of Neuroscience and Medicine, Forschungszentrum Jülich, Germany. • Carlos Cernuda, Data Analysis & Cybersecurity, Faculty of Engineering, Mondragon Unibertsitatea, Bilbao, Spain. • Jakob Jordan, Department of Physiology, University of Bern, Switzerland. • Jenni Rinker, Department of Wind Energy, Technical University of Denmark, Roskilde, Denmark. • Lisa Schwetlick, Experimental and Biological Psychology, Universität Potsdam, Germany. • Pamela Hathway, GfK, Nuremberg, Germany. • Pietro Berkes, NAGRA Kudelski, Lausanne, Switzerland. • Rike-Benjamin Schuppner, Institute for Theoretical Biology, Humboldt-Universität zu Berlin Germany. • Seetha Krishnan, Department of Neurobiology and Institute for Neuroscience, University of Chicago, Chicago, USA. • Tiziano Zito, Department of Informatics, Technische Universität Berlin, Germany. • Zbigniew Jędrzejewski-Szmek, Red Hat Inc., Warsaw Poland. Organizers ========== Head of the organization for ASPP-LatAm and responsible for the scientific program: • Carlos Echeverria Serur, Department of Psychology, Humboldt-Universität zu Berlin, Germany Organization team in Mexico: • Cristina Muzquiz Fragoso, DGTIC, Universidad Nacional Autónoma de Mexico • Miguel Angel Villanueva Velez, DGTIC, Universidad Nacional Autonoma de Mexico • Patricia Garces Natera, DGTIC, Universidad Nacional Autonoma de Mexico Website: https://latam.aspp.school Contact: latam(a)aspp.school

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New data management & sharing resources on the INCF portal!
by INCF 13 Feb '23

13 Feb '23

Data sharing is on everyone’s mind right now, especially since NIH put their data managing and sharing policy into effect on January 25. At INCF, we have been working to facilitate data sharing, reuse, and reproducibility in neuroscience since our inauguration in 2005. Our current focus is on developing, evaluating, and endorsing standards and best practices that facilitate data sharing, open, FAIR, and citable neuroscience, as well as providing the community with resources and training opportunities on how to implement these standards and best practices. We have just added new FAIR resources to our portal. Here is a summary of the resources INCF offers to researchers on the fundamentals of data sharing and data management: - The FAIR roadmap <http://bit.ly/FAIRRoadmapINCF> - The INCF Standards and Best Practices Portfolio <http://bit.ly/INCFportfolioSBPs> - The INCF Infrastructure Portfolio <http://bit.ly/INCFInfraPortfolio> - The INCF Training Suite <https://bit.ly/INCFTrainingSuite> - Community <https://www.incf.org/services/community-building> & capacity <https://www.incf.org/services/capacity-building> building - FAIR consulting services <https://www.incf.org/services/fair-consulting-services> Learn more <http://bit.ly/INCFsNewResources> about these resources INCF is a member organization - an active global network of neuroscientists, data scientists, and tool developers that come together to interact and receive feedback in order to solve large and small problems around data sharing and standardization. This network is our greatest resource and it’s open for participation: we have individual and group memberships, both for academic/non-profit groups and for companies in related fields. Many of our working groups are also open to new members. Want to get involved? Contact us at info(a)incf.org! /The INCF Team

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Barcelona summer school for Advanced Modelling of Behavior (BAMB!), July 19-27, 2023
by Alexandre Hyafil 13 Feb '23

13 Feb '23

The Barcelona summer school for Advanced Modelling of Behavior (BAMB! <http://www.bambschool.org>) teaches advanced techniques in model-based analysis of behavior (humans and other species) to cognitive and computational neuroscientists at PhD and early career levels. This will be achieved through structured lectures, talks, hands-on tutorials and group projects aimed at making knowledge obtained directly applicable to the participants' own research. We want the trainees to acquire both the conceptual basis and the technical skills that will enable them to pursue a full modelling approach on their own when they come back to their lab. The course is intended for PhD students and postdocs in cognitive, systems and computational neuroscience with a solid background in computational/quantitative analysis to benefit maximally from the advanced training offered by the course. Proficiency in either Python or Matlab is also required. We seek a nice blend of experimentalists (cognitive psychology / neuroscience) and theoreticians (with or without experience in cognitive modeling). Scientists from underrepresented groups and countries are especially encouraged to apply. The school is organized by the Centre de Recerca Matemática <http://www.crm.cat>. A limited number of course fee waivers will be available. Organizers: Chris Summerfield (Oxford / Deepmind) Marion Rouault (Paris Brain Institute) Klaus Wimmer (CRM, Barcelona) Heike Stein (ENS, Paris) Alex Hyafil (CRM, Barcelona) Confirmed Faculty: Anne Collins (UC Berkeley) Elaine Corbett (UC Dublin) Maria Eckstein (Deepmind) Alex Hyafil (CRM, Barcelona) John Krakauer (John Hopkins) Marion Rouault (Paris Brain Institute) Chris Summerfield (Oxford / Deepmind) Valentin Wyart (ENS Paris) Klaus Wimmer (CRM, Barcelona) Dates and location: July 19-27, downtown Barcelona, Spain Applications are open until March 15. Please see the course website for further details: www.bambschool.org.

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Registration is now open for IBD 2023 - Interpretable Brain Data Workshop
by Gonzalo Uribarri 13 Feb '23

13 Feb '23

Dear all, If you're interested in exploring the latest techniques for non-invasive human brain data analysis, we cordially invite you to attend the Interpretable Brain Data Workshop 2023 (IBD 2023) in Stockholm, Sweden on June 8th and 9th. Leading researchers will showcase the state-of-the-art methods for analyzing and interpreting MRI and E/MEG data, offering insights from both theoretical and experimental perspectives. The event is *free to attend* and you can participate either *in person or virtually*. The confirmed keynote speakers for the event are: - *Prof. Gustavo Deco*, Research Professor at ICREA and Professor at the Pompeu Fabra University. - *Prof. Peter Fransson*, Karolinska Institute, Stockholm, Sweden. - *Prof. Axel Thielscher*, DTU and DRCMR, Copenhagen, Denmark. This is a unique opportunity to learn from world-renowned experts and connect with researchers from all over the world. You can find all the details, including the full schedule, speaker list, and registration link, on the official IBD 2023 webpage at https://ibd2023.carrd.co/. We look forward to seeing you there! Best regards, The IBD 2023 Organizing Committee: Gonzalo Uribarri Christoffer Olsson Andreas Gerhardson Pascal Helson

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Postdoctoral positions in computational neuroscience in New York - Albert Einstein College of Medicine
by Ruben Coen-Cagli 10 Feb '23

10 Feb '23

The Laboratory for Computational Neuroscience<https://sites.google.com/site/rubencoencagli> (Coen-Cagli lab) invites applications for postdoctoral positions in the Department of Systems and Computational Biology and Department of Neuroscience at Albert Einstein College of Medicine (Einstein) in the Bronx, New York City. Our lab studies how sensory systems interpret the surrounding environment. Our goal is to reveal the strategies and algorithms used by our visual system to parse the complex, dynamic inputs received during natural vision, and to elucidate how populations of visual-cortical neurons represent and transmit visual information to support perceptual experience. We integrate theories of probabilistic neural coding, machine learning and natural image statistics, visual psychophysics, and neurophysiology through collaborations. Currently active projects include: perceptual grouping and segmentation<https://reporter.nih.gov/search/-7u_GOe7Bkaedp3a-T-tDw/project-details/1001…>, processing of natural images in the visual cortex<https://reporter.nih.gov/search/-7u_GOe7Bkaedp3a-T-tDw/project-details/1046…>, development of statistical tools to study interactions between neurons<https://reporter.nih.gov/search/-7u_GOe7Bkaedp3a-T-tDw/project-details/1048…>, and testing theories of visual processing in ASD<https://www.einsteinmed.edu/centers/iddrc/opportunities/pilot-feasability-a…>. There will be opportunities for substantial interactions with and travel to the collaborating labs. Further details about the application can be found here<https://drive.google.com/file/d/1eYeyH4Uf4aoApRBdKye4jmFR4P5vLhXN/view?usp=…> and here<https://drive.google.com/file/d/13hp-5DmnNHtRoA4hMwn7Kc0tWp_6JCwa/view>. Further details about our research can be found here<https://sites.google.com/site/rubencoencagli>. Please email ruben.coen-cagli(a)einsteinmed.edu for any questions about the positions. The Albert Einstein College of Medicine is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information. Einstein seeks candidates whose skills, and personal and professional experience, have prepared them to contribute to our commitment to diversity and excellence, and the communities we serve. Ruben Coen Cagli, PhD Associate Professor Department of Systems and Computational Biology, and Dominick Purpura Department of Neuroscience Albert Einstein College of Medicine 1300 Morris Park Ave. Price 353B Bronx, 10461. NY office: +1.718.678.1150 web: https://sites.google.com/site/rubencoencagli/<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsites.goo…>

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Transylvanian Experimental Neuroscience Summer School (TENSS 2023)
by Tomas Hromadka 09 Feb '23

09 Feb '23

Dear colleagues, Please find below an announcement about the 11th edition of the Transylvanian Experimental Neuroscience Summer School (TENSS 2023). We would be very grateful if you forwarded this announcement to potentially interested people. We have started a worldwide initiative to train young brain researchers, from both developed and less developed countries, in understanding and using the most advanced tools in brain research today. We do this in an idyllic location, without any pre-existing infrastructure, where students and instructors alike enjoy the adventure, work hard, and build sophisticated research labs from scratch. The main objective of TENSS is to provide participants top-level, hands-on training in experimental techniques used in neuroscience, from optical, electrophysiological, and behavioural methods to advanced data analysis and machine learning. The philosophy of the school is learning by doing and while doing so, openly sharing ideas and expertise. This is TENSS, the Transylvanian Experimental Neuroscience Summer School: June 1-21, 2023, Pike Lake, Transylvania, Romania – https://tenss.ro/. • 3 weeks of 24/7 hands-on practical and theoretical courses in building, debugging, using and interpreting data from cutting-edge experimental methods in modern neuroscience. • A select group of the best 12-14 applicants: for the 2022 edition, top 14 were selected from an excellent pool of more than 100 applicants from all over the world. • A wide collection of experts: ~29 lecturers and 16 dedicated teaching assistants from brain research institutes in the USA, UK, Germany, France, Poland, Romania, India, Switzerland, Portugal, Hungary, and Slovakia. • A knowledge base of Open-Source solutions to complex problems in brain research. Coursework will take place in a land of myth and legend, beyond large forests (Transylvania), on the shores of a picturesque natural reserve called Pike Lake. Applications are welcome from interested (and interesting) graduate students and postdocs. Please note that there is a significant number of fee waivers and travel support grants available for supporting our applicants. Application deadline – March 5th, 2023 Notification of acceptance – April, 2023 Summer School – June 1-21st, 2023 Invited lecturers (tentative): Athena Akrami – Sainsbury Wellcome Centre, UCL, UK Upinder Bhalla – National Centre for Biological Sciences, India Federico Carnevale – DeepMind Technologies, London, UK Ann Clemens – University of Edinburgh, UK Ashesh Dhawale – Centre for Neuroscience, IISc Bangalore, India Michael Dickinson – California Institute of Technology, USA Florian Engert – Harvard University, USA Nadine Gogolla – Max Planck Institute of Psychiatry, Germany Sonja Hofer – Sainsbury Wellcome Centre, UCL, UK Helen Xun Hou – Cold Spring Harbor Laboratory, USA Tomáš Hromádka – Slovak Academy of Sciences, Slovakia Benjamin Judkewitz – Einstein Center for Neuroscience, Germany Georg Keller – Friedrich Miescher Institute, Switzerland Emilie Mace – Max Planck Institute of Neurobiology, Germany Eve Marder – Brandeis Unversity, USA Hannah Monyer – University of Heidelberg, Germany Tom Mrsic-Flögel – Sainsbury Wellcome Centre, UCL, UK Bence Ölveczky – Harvard University, USA Ruben Portugues – Max Planck Institute of Neurobiology, Germany Tobias Rose – University of Bonn, Germany Wolf Singer – Ernst Strüngmann Institute, Germany Daniela Vallentin – Max-Planck-Institute for Ornithology, Germany Jakob Voigts – HHMI, Janelia Research Campus, USA Chris Xu – Cornell University, USA Petr Znamenskiy – Francis Crick Institute, UK Tony Zador – Cold Spring Harbor Laboratory, USA Teaching Assistants & Organizing Team: Harald Bârzan Antonin Blot Rob Campbell Andrei Ciuparu Loredana Dan Medorian Gheorghiu Matías Goldin Priyanka Gupta Yiran He Ana Maria Ichim Mitra Javadzadeh Mateusz Kostecki Fred Marbach Vasile V. Moca Adriana Nagy-Dăbâcan Jon Newman Cosmina Pavel Bruno Pichler Laura Rus Nacho Sanguinetti Pavithraa Seenivasan Iuliu Vasilescu Anqi Zhang Best regards, TENSS Organizing Committee contact [at] tenss.ro

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Interdisciplinary Computational Social Neuroscience Postdoc Opening at Duke University
by Dr Jana Schaich Borg, Ph.D. 09 Feb '23

09 Feb '23

Interdisciplinary Computational Social Neuroscience Postdoc Opening at Duke University Our group has an opening for a postdoctoral position in the Social Science Research Institute, Duke Institute for Brain Sciences, and Department of Mathematics at Duke University. The focus of the postdoc position is on developing novel interpretable algorithms for identifying social interaction motifs and their typical temporal and hierarchical relationships during natural interactions. The methodological tools developed will first be applied to a highly novel dataset of human social interaction videos with associated behavioral and clinical outcomes. The methods will then be applied to the lab's datasets involving human MRI data during social decisions, human physiological and EEG data during social interactions, videos of rodent social interactions, or rodent LFP data during social interactions, depending on the applicants' primary interests and background. This is highly interdisciplinary position and line of research, so successful applicants may come from a variety of fields, including (but not limited to) neuroscience, cognitive science, mathematics, computer science, electrical engineering, biomedical engineering, and (bio)statistics. However, all applicants should have excellent coding skills, extensive experience with data analysis, and at least some experience with statistical modeling and prediction. Experience with image processing is ideal, but not required. Applicants who want to use the postdoc to deepen or broaden their existing skill sets, applications, or domain knowledge are welcomed. Neuroscientists who want mentorship in mathematical theory or engineers/mathematicians/statisticians who want mentorship in how to apply their skills to an exciting and dynamic field with theoretical, clinical, and commercial implications are particularly encouraged. The applicant will be co-mentored in neuroscience, social behavior theory, mathematical theory development, applied analysis, and job placement by Dr. Schaich Borg (Duke Institute for Brain Science, Social Science Research Institute) and Dr. Hau-Tieng Wu (Departments of Mathematics and Statistics). Timeline: The postdoc could start immediately, but later start dates are also available for appropriate candidates. Teaching: The position does not require any teaching, but teaching opportunities and teaching mentorship are available if the candidate is interested. Contact: Interested applicants should contact Dr. Schaich Borg (js524(a)duke.edu) through email, and include a CV, statement of research interests, and names of three referees that can provide letters of recommendation in the future, if needed. We are strongly committed to a diverse academic environment and place high priority on attracting underrepresented candidates. Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas-an exchange that is best when the rich diversity of our perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all individuals are respected, and that all voices are heard. All members of our community have a responsibility to uphold these values.

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Applications for 2023-24 entry OPEN:: MSc in Intelligent Vision, University of Lincoln (Lincoln, UK)
by Vassilis Cutsuridis 06 Feb '23

06 Feb '23

********************************************************************************** The MSc in INTELLIGENT VISION at the University of Lincoln (UK) ********************************************************************************** is now ACCEPTING APPLICATIONS for 2023-24 ENTRY. Note that places are limited and will be allocated on a first-come first-served basis. If you are considering this programme, we recommend applying now rather than later to avoid disappointment. This cutting-edge Masters course builds on the multi-disciplinary and strong research profiles of our staff. It equips students with the advanced knowledge and skills needed to develop the innovative solutions required by the emerging global AI Vision industry providing them also with an opportunity to consolidate their skills in a practical research project, possibly carried out in collaboration with a partner from industry. HOW TO APPLY ============= Download the online application from the following link and fill out all relevant information: https://www.lincoln.ac.uk/media/responsive2017/studywithus/postgraduatestud… Then click on the following link: https://uol.t1cloud.com/T1Default/CiAnywhere/Web/UOL/StudentCore/StudentApp… and follow the instructions. COURSE OUTLINE =============== This is a one-year (full-time) or two-years (part-time) MSc degree programme, consisting of taught courses (105 credits) plus a seminar based course (15 credits) and a research project and dissertation (60 credits). (Note: students who need a Tier-4 VISA to study in the UK can only register for the full-time pathway). It is designed for students with a good degree in physical (computer science, mathematics, physics, engineering) sciences, however, individuals with different backgrounds but commensurate experience will also be considered. The core modules of this course include: (a) Advanced artificial intelligence (theoretical fundamentals and practical applications of decision-making, problem-solving and learning abilities in software agents) (b) Advanced machine learning (theoretical fundamentals and practical application of supervised, unsupervised, reinforcement and evolutionary learning) (c) Computer Vision (applications of computer vision in object recognition/tracking, medical image analysis, multimedia indexing and retrieval and intelligent surveillance systems) (d) Neural Computing (fundamentals of an emergent specialised area of computer science that is concerned to describe how the brain computes by simplifying neuronal biology to a set of equations) (e) Big Data Analytics and Modelling (a range of aspects in collecting, transforming, processing, analysing and make inferences out of large amounts of data, which can either be signals or visual data) (f) Applied signal and image processing (a range of aspects in capturing, processing, analysing and interpreting n-dimensional signal and image content) (g) Research methods (fundamental skills and background knowledge students need to undertake a research project including: surveying literature; selecting and justifying a research topic; planning of research; selection of appropriate research methods; evaluation of research; presentation and reporting of research; and legal, social, ethical and professional considerations) (h) Frontiers in machine learning and computer vision (a seminar based module about the state of the art in machine learning and computer vision research, including an understanding of the theoretical developments and current applications in the field) (i) Research project The final research project can be carried out ‘in house’ or in collaboration with an external partner, either from academia or industry. For samples of previous MSc projects, visit: https://www.lincoln.ac.uk/course/intvisms/ under "Student Project Work" LINKS WITH INDUSTRY =================== The programme has active links with a number of collaborators from industry, including representatives from international companies with headquarters in UK, Greece, Germany, Spain, China, and US. Carrying out your final project in collaboration with one of our industry partners or securing a placement with them after completion of your degree will enable you to acquire modern technical skills that are much in demand, paving the way for employment opportunities and making you very competitive on the job market. For any further information, including funding opportunities and tuition fees, please visit: https://www.lincoln.ac.uk/studywithus/postgraduatestudy/feesandfunding/ Here is what our alumni have to say about this course: https://www.lincoln.ac.uk/course/intvisms/ For any other specific questions, please do not hesitate to get in touch. Kind regards, Vassilis Cutsuridis -- Programme Leader, MSc in Intelligent Vision Senior Lecturer School of Computer Science University of Lincoln Brayford Pool Lincoln LN6 7TS, UK https://staff.lincoln.ac.uk/vcutsuridis ******************************************************************************

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[EEG] PhD / Research Assistant position at University of Coimbra, Portugal
by maritametzler＠posteo.de 06 Feb '23

06 Feb '23

We are searching for a PhD candidate working on human-robot collaboration. Please have a look into the description below and in case of interest contact Art Pilacinski (art.pilacinski(a)gmail.com) or Sergi Bermudez I Badia (sergi.bermudez.badia(a)gmail.com) Best, Marita ---------- Forwarded message --------- From: Art Pilacinski <art.pilacinski(a)gmail.com> Date: Mon, Feb 6, 2023 at 1:05 PM Subject: [EEG] PhD / Research Assistant position at University of Coimbra, Portugal To: <spm(a)jiscmail.ac.uk> Cc: Sergi Bermudez i Badia <sergi.bermudez.badia(a)gmail.com> Hi everyone, We are searching for an enthusiastic candidate to work on a cool project using human biomarkers (EEG, eye tracking, EMG) and virtual reality to advance collaborative robotics. The project will take part at University of Coimbra and at University of Madeira, with collaborations in Germany and Spain. The position is initially for 3 years but multiple extension options are available. See more details here: https://proactionlab.fpce.uc.pt/en/news-entry/we-are-hiring- Please, feel free to forward this ad to whoever might be interested. Thanks, Art -- Art Pilacinski Researcher | Inv. Assist. Professor Klaes Lab | Proaction Lab Ruhr-University Bochum | University of Coimbra Bochum, Germany | Coimbra, Portugal klaeslab.de | proactionlab.fpce.uc.pt

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