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PhD Studentship – Modelling cortico-subcortical oscillatory connectivity.
by Dimitris Pinotsis Feb. 18, 2020

Feb. 18, 2020

PhDStudentship – Modelling cortico-subcortical oscillatory connectivity. Applicationsare invited for a 3-year funded PhD studentship in the Wellcome Centre forHuman Neuroimaging (https://www.fil.ion.ucl.ac.uk/) under the supervision ofDr. Vladimir Litvak and Dr. Simon Farmer and in collaboration with theComputational Neuroscience Group (CNS, https://www.upf.edu/web/cns) led byProf. Gustavo Deco, at the Center for Brain and Cognition(https://www.upf.edu/web/cbc), Pompeu Fabra University (Barcelona, Spain). The position is part of the EU-fundedInnovative Training Network euSNN (“European School of Network Neuroscience”)and available, with full-time employment, for a duration of 3 years withimmediate start. TheeuSNN Innovative Training Network integrates 16 leading European groups innetwork neuroscience and 7 companies to train students who want to pursue asuccessful career in the field of network neuroscience. The euSNN trainingprogramme offers a unique combination of experimental, analysis and modellingapproaches. Exploiting intense collaborations between experimental, theoreticaland clinical groups, euSNN links basic research on large-scale brain dynamicswith new pathophysiological approaches and clinical applications. The euSNNnetwork is coordinated by Prof. Dr. Andreas K. Engel. Further information onthe euSNN network can be found at http://eusnn.eu. Project details Deep Brain Stimulation(DBS) is an effective treatment method for a range of neurological andpsychiatric conditions. It involves placing electrodes deep in a patient’sbrain, usually in precisely targeted subcortical nuclei. DBS surgery affords aunique opportunity to study the neural activity of these nuclei via recordingof local electrical signals known as local field potentials (LFP). Our grouppioneered simultaneous recording of subcortical LFP with non-invasive wholebrain imaging using magnetoencephalography (MEG). This makes it possible to mapout cortico-subcortical oscillatory coherent networks which have characteristicfrequencies and cortical topographies for each subcortical target. Over theyears we collected data from several different subcortical nuclei andcharacterised their oscillatory networks. The aim of the proposed project is toestablish a modelling framework which could accommodate these findings and makequantitative predictions for future experiments. This will require extendingexisting models of cortical dynamics and integrating information fromadditional imaging modalities such as functional MRI and Diffusion TensorModelling (DTI). The euSNN training networkoffers exciting and unique opportunities for the student to pursue this projectincluding interactions with top experts in neuroimaging brain modelling andexposure to several different modelling frameworks and approaches that thestudent will have to master and integrate to achieve the project’s goals. Theremight also be opportunities towards the end of the project to test some of thepredictions experimentally. In addition, the student will have a chance to workon secondments with commercial companies on topics relevant to the project. Funding notes The starting date can beany date between being offered the position and 1st October 2020 andthe contract is for 36 months. The studentship includes UK/EU tuition fees anda stipend along with additional funds to cover travel and accommodation duringsecondments and network activities. Overseas fees cannot be covered. Entry requirements Applicants should have an HonoursDegree (minimum 2:1) in a quantitative discipline: Physics/Mathematics/Engineering/Computer science, strong mathematical background and interestin neuroscience. Knowledge of scientific programming languages, particularlyMatlab, background in modelling complex physical systems and a relevant Mastersqualification is desirable. Applicants should be willing to travel to attendthe network activities and spend prolonged periods of time (up to a few monthsat a time and at least 8 months in total) doing secondments outside the UK. Applicantsmust not have been residing in the UK for more than 12 months prior to thestart of the appointment. Deadline 30th April 2020. Shortlisted candidates will beinterviewed in May. How to apply: Applicants should submit 1)a CV, 2) a 1-page statement detailing why you want to do the PhD, motivation,interest and suitability for the project, 3) a copy of your strongest singlepiece of academic work (e.g. thesis, publication), and 4) contact details oftwo referees. Please ensure that each document is clearly labelled with yoursurname. Please send all documents to Kamlyn Ramkissoon k.ramkissoon(a)ucl.ac.ukby 30th April 2020.Interviews will be held in May 2020. Informal enquiries are welcome to Dr Vladimir Litvak (email: v.litvak(a)ucl.ac.uk)

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Postdoctoral position in functional neuroimaging
by Alessandro Gozzi Feb. 18, 2020

Feb. 18, 2020

The Functional Neuroimaging Laboratory (https://www.iit.it/research/lines/functional-neuroimaging) at Istituto Italiano di Tecnologia (IIT) in Rovereto (Italy) is looking for a Postdoctoral scientist interested in studying the neural basis of functional connectivity disruption in autism. Our research is aimed at identifying the general neural and cellular principles governing the assembly of brain connectivity, and its breakdown in developmental disorders such as autism. We address these questions by mapping functional connectivity alterations in people with autism and model organisms harboring autism-associated genetic etiologies. For reference to recent work relevant to this position, please see Gutierrez-Barragan et al., Current Biology (2019) and Bertero et al., Brain (2018). The successful candidate must have a PhD in cognitive neuroscience, physics, neuroinformatics or equivalent, a proven record in the analysis of functional images of the mammalian brain, plus a sound knowledge of signal processing and statistical methods applied to brain imaging. We evaluate candidates that are proactive, highly-motivated, and who are willing to interact with both experimental and computational neuroscientists. The IIT center in Rovereto is actively expanding its infrastructure for systems level neuroscience research, and is inserted both in the vibrant community of the IIT and that of CIMeC (www.cimec.unitn.it) within the University of Trento, which specializes in cognitive neuroscience. Please submit your application, including a detailed CV with a brief research statement, a cover letter and name and contacts of 2 referees, by email to alessandro.gozzi(a)iit.it, quoting "Postdoctoral position in neuroimaging - CB 78211" in the email subject. The first deadline for applications is March 20th, 2020. This position will remain open until filled. Salary will be commensurate with qualifications and experience. Fondazione Istituto Italiano di Tecnologia (http://www.iit.it) is a non-profit institution created with the objective of promoting technological development and higher education in science and technology. Research at IIT is carried out in highly innovative scientific fields with state-of-the-art technology. Istituto Italiano di Tecnologia is an equal opportunity employer that actively seeks diversity in the workforce. Please note that the data that you provide will be used exclusively for the purpose of professional profiles' evaluation and selection, and in order to meet the requirements of Istituto Italiano di Tecnologia. Your data will be processed by Istituto Italiano di Tecnologia, based in Genoa, Via Morego 30, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security. Please also note that, pursuant to articles 15 et. seq. of European Regulation no. 679/2016 (General Data Protection Regulation), you may exercise your rights at any time by contacting the Data Protection Officer (phone +39 010 71781 - email: dpo[at]iit.it) Contacts Alessandro Gozzi alessandro.gozzi(a)iit.it<mailto:alessandro.gozzi@iit.it> Twitter: Gozzi_Ale Alessandro Gozzi, PhD Senior Scientist, Group Leader Functional Neuroimaging Laboratory Istituto Italiano di Tecnologia Center for Neuroscience and Cognitive Systems @ UNITN Corso Bettini 31, 38068 Rovereto, Italy Tel: +39 0464 808 701

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Three permanent associate professor positions in data science
by Hans Ekkehard Plesser Feb. 18, 2020

Feb. 18, 2020

The Faculty of Science and Technology at the Norwegian University of Life Sciences is expanding its data science activities in research and education and invites applications for Three permanent associate professor positions in data science with focus on * Machine learning for the 21st century (https://www.jobbnorge.no/en/available-jobs/job/183310/associate-professor-i…) * Data management for a data science world (https://www.jobbnorge.no/en/available-jobs/job/183306/associate-professor-i…) * Value-oriented deployment of data science (https://www.jobbnorge.no/en/available-jobs/job/183315/associate-professor-i…) Closing date for all positions is 22 March 2020. For details and to apply, please see the full announcements for the positions linked above. Background information about us, our programs and our expectations is available in https://arken.nmbu.no/~plesser/NMBU_ThreeAssocProfsDataScience_AdditionaInf… Best regards, Hans Ekkehard Plesser -- 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<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

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Grandmother cells a failed concept? Or is Barlow right that grandmother cells exist and “can now be recorded from and studied reliably?"
by Asim Roy Feb. 16, 2020

Feb. 16, 2020

Ann-Sophie Barwich recently published an article in Frontiers in Neuroscience titled “The Value of Failure in Science: The Story of Grandmother Cells in Neuroscience” (https://www.frontiersin.org/articles/10.3389/fnins.2019.01121/full) where she argues for the need for failure analysis in science and, in the context of neuroscience, analyzed the grandmother cell concept as a failed one. Although I was one of the reviewers who endorsed the article for publication (publication of alternative viewpoints is essential in science), I felt that Barwich’s arguments against grandmother cells were deeply flawed. I point out these flaws in a Commentary in Frontiers in Neuroscience: “Commentary: The Value of Failure in Science: The Story of Grandmother Cells in Neuroscience:” https://www.frontiersin.org/articles/10.3389/fnins.2020.00059/full I think Reddy and Thorpe’s 2014 article clears the confusion about concept cells. With Reddy and Thorpe’s characterization of concept cells, one would find no difference between concept cells and grandmother cells. And that’s essentially what I have done in the Commentary – show that concept cells and grandmother cells have identical properties. I also point out in the Commentary that it’s a false claim by Barwich (and in other prior articles that Barwich references) that concept cells can be part of a sparse population coding scheme. Given that concept cells have “meaning” on a stand-alone basis, they can’t be part of any population coding scheme. And it’s also a false claim in Barwich that grandmother cells do not use associative learning, because grandmother cells have always been characterized as “multimodal” going all the way back to Gross (2002). In addition, the neurophysiological evidence on multisensory neurons clearly point to a single-cell based abstract cognitive system in the brain, as claimed by Roy (2017). Overall, concept cell findings confirm the prediction of Barlow (2009)<https://www.frontiersin.org/articles/10.3389/fnins.2020.00059/full#B1> that grandmother cells exist and “can now be recorded from and studied reliably.” YOU CAN EMAIL ME IF YOU WANT TO JOIN A DISCUSSION GROUP ON THIS TOPIC. Barlow, H. B. (2009). “Grandmother cells, symmetry, and invariance: how the term arose and what the facts suggest,” in The Cognitive Neurosciences, 4th Edn., ed M. Gazzaniga (Cambridge, MA: MIT Press), 309–320. Reddy, L., and Thorpe, S. J. (2014). Concept cells through associative learning of high-level representations. Neuron 84, 248–251. doi: 10.1016/j.neuron.2014.10.004 Roy, A. (2017). The theory of localist representation and of a purely abstract cognitive system: the evidence from cortical columns, category cells, and multisensory neurons. Front. Psychol. 8:186. doi: 10.3389/fpsyg.2017.00186

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job post: machine learning research scientist at NIMH
by Francisco Pereira Feb. 15, 2020

Feb. 15, 2020

*** HIRING: machine learning research scientist The Machine Learning Team at the National Institute of Mental Health (NIMH) in Bethesda, MD, has an open position for a machine learning research scientist. The NIMH is the lead federal agency for research on mental disorders and neuroscience, and part of the National Institutes of Health (NIH). *** About the NIMH Machine Learning Team Our mission is to help NIMH scientists use machine learning methods to address a diverse set of research problems in clinical and cognitive psychology and neuroscience. These range from identifying biomarkers for aiding diagnoses to creating and testing models of mental processes in healthy subjects. We work with many different data types, including very large brain imaging datasets from various imaging modalities, behavioral data, and picture and text corpora. We have excellent computational resources, both of our own (tens of GPUs for deep learning) and shared within the NIH (a cluster with hundreds of thousands of CPUs, and hundreds of GPUs). As a machine learning research group, we develop new methods and publish in the main machine learning conferences (e.g. NeurIPS and ICLR), as well as in psychology and neuroscience journals. Many of our problems require devising research approaches that combine imaging and non-imaging data, and leveraging structured knowledge resources (databases, scientific literature, etc) to generate explanations and hypotheses. You can find more about our work and publications at https://cmn.nimh.nih.gov/mlt *** About the position We are seeking candidates who are capable of combining machine learning, statistical, and domain-specific computational tools to solve practical data analysis challenges (e.g. designing experiments, generating and testing statistical hypotheses, training and interpreting predictive models, and developing novel models and methods). Additionally, candidates should be capable of visualizing and communicating findings to a broad scientific audience, as well as explaining the details of relevant methods to researchers in a variety of domains. Desirable experience that is not required, but will be considered very favorably: - neuroimaging data processing and analysis (any MRI modality, as well as MEG/EEG) - Bayesian statistical modelling - natural language processing / structured data such as EHR or questionnaires Finally, you should have demonstrable experience coding in languages currently used in data-intensive, scientific computing, such as Python, MATLAB or R. This is an ideal position for someone who wants to establish a research career in method development and applications driven by scientific and clinical needs. Given our access to a variety of collaborators and large or unique datasets, there is ample opportunity to match research interests with novel research problems. We also maintain collaborations outside of the NIH, driven by our own research interests. If you would like to be considered for this position, please send francisco.pereira(a)nih.gov a CV, with your email serving as cover letter. If you already have a research statement, please feel free to send that as well. There is no need for reference letters at this stage. Other inquiries are also welcome. Thank you for your attention and interest!

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Call for Applications: EADM Summer School on Learning and Decision Making
by Hrvoje Stojic Feb. 15, 2020

Feb. 15, 2020

APPLICATIONS ARE NOW OPEN (until 15 March 2020)! Dates: 8-15 July, 2020 Location: Universitat Pompeu Fabra, Barcelona, Spain Topic: Learning and Decision Making Eligibility to Apply: Early career researchers Further details available at: https://ldmss.org APPLICATION INSTRUCTIONS: https://ldmss.org#apply The 5th EADM Learning and Decision Making summer school will take place from the 8th to the 15th of July in Barcelona, Spain. It will cover a wide range of topics related to learning and decision making, including reinforcement learning, sampling biases, decisions from experience, function learning, category learning and social learning. Participants will receive advanced training and hands-on tutoring on various computational modeling approaches in learning and decision making from experts in the field and will get feedback on their latest research ideas in poster sessions. The program will also include social and group activities in the beautiful city of Barcelona. Confirmed faculty include: Mirta Galesic (Santa Fe Institute) Maarten Speekenbrink (University College London) Johannes Müller-Trede (IESE Business School) Henrik Olsson (Santa Fe Institute) G. Elliot Wimmer (University College London) Mehdi Keramati (City University) Jörg Rieskamp (University of Basel) Elizaveta Konovalova (Max Planck Institute for Human Development) Cecília Nunes (Universitat Pompeu Fabra) More coming soon! The organization team: Gael Le Mens (Universitat Pompeu Fabra) Emmanouil Konstantinidis (University of Warwick) Hrvoje Stojic (University College London) Pantelis P. Analytis (University of Southern Denmark) Mikhail Spektor (Universitat Pompeu Fabra) Feel free to send us any questions at: ldmss(a)protonmail.com or on Twitter @ldmsschool. ----------------------------- Hrvoje Stojic, PhD Postdoctoral researcher University College London Website: [https://hstojic.re/](http://hstojic.re/)

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[ICDL-2020] Call for Tutorials
by Miguel Solís Feb. 15, 2020

Feb. 15, 2020

Apologies if you receive multiple copies of this call due to cross-posting, please help to distribute among possible interested contributors. CALL FOR TUTORIALS: 10th IEEE International Conference on Development and Learning (ICDL) 7th-10th September 2020, Valparaiso, Chile Web page: https://cdstc.gitlab.io/icdl-2020/ An IEEE Computational Society-sponsored conference ==== Important Dates ==== Tutorial Proposals Open: 15th February 2020 Tutorial Proposals Deadline: 30h April 2020 Tutorial Proposals Notification: 15th May 2020 ==== Overview ==== We invite experts in different areas to organize a tutorial. The goal of tutorials is to provide insights into specific topics through hands-on training and interactive experiences or in-depth state of the art review. Tutorial organizers have several responsibilities, including activities scheduling, publicizing and providing the content on time. ICDL will support the organization with rooms, audio-visual equipment and coffee breaks. ==== Scope and Topics ==== The main list of topics of interest includes, but not limited to: - principles and theories of development and learning; - development of skills in biological systems and robots; - nature vs nurture, developmental stages; - models on the contributions of interaction to learning; - verbal, non-verbal and multi-modal interaction; - models on active learning; - architectures for lifelong learning; - emergence of body and affordance perception; - analysis and modelling of human motion and state; - models for prediction, planning and problem solving; - models of human-human and human-robot interaction; - emergence of verbal and non-verbal communication; - epistemological foundations and philosophical issues; - robot prototyping of human and animal skills; - ethics and trust in computational intelligence and robotics; - social learning in humans, animals, and robots. ==== Submission format ==== Proposals should be maximum of two pages long following the standard IEEE conference style. Proposals should be submitted in PDF format by email to icdl2020(a)ac3e.cl with subject “[Tutorials]”. Proposals should specify the following: Title Organizers Duration (half-day or full-day) A brief description of the topics to be covered Tentative program Target audience and interested groups Website Any logistic requirements such as poster stands, computers, projector, etc. For more information about the conference, travel grants, social events, etc. visit the conference webpage under https://cdstc.gitlab.io/icdl-2020/ ==== Organizing committee ==== General Chairs: Giulio Sandini, and Javier Ruiz-del-Solar Program and Finance Chairs: Nicolás Navarro-Guerrero, and María-José Escobar Bridge Chairs: Minoru Asada, Frédéric Alexandre, and Linda Smith Publicity Chairs: Carmelo Bastos, Maya Cakmak, Angelo Cangelosi, Yukie Nagai, and Emre Ugur Publication Chairs: Pablo Barros, and Haian Wu Tutorials and Workshops Chair: Miguel Solis Travel and Registration Awards Chair: Francisco Cruz Local chairs: Mauricio Araya Webpage Chairs: Cristóbal Nettle, and Patricio Castillo Graphics: Camila Angel Alfaro Best regards from the organizing committee,

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Postdoctoral fellow for an international collaboration
by Lucia Melloni Feb. 14, 2020

Feb. 14, 2020

Dear all, There is an exciting opportunity for a 2-3 years senior post-doctoral research position to work with Michael Pitts at Reed College, Portland Oregon, USA (https://www.reed.edu/psychology/scalp/) and Liad Mudrik at Tel Aviv University, Tel Aviv, Israel (http://www.mudriklab.tau.ac.il) (location flexible in one of the two labs). Project: International adversarial collaboration <https://science.sciencemag.org/content/366/6463/293?utm_campaign=toc_sci-ma…> on the neural basis of visual consciousness, aimed at testing key predictions of integrated information theory and global neuronal workspace theory. Collaborators include: Lucia Melloni, Stanislas Dehaene, Giulio Tononi, Christof Koch, David Chalmers, Hal Blumenfeld, Floris de Lange, Ole Jensen, Gabriel Kreiman, Huan Luo, Francis Fallon, and others. Required skills: • expertise in advanced data analysis for as many of the following techniques as possible:EEG/MEG, fMRI, ECoG • experience and interest in managing large datasets • experience and interest in cloud-based or local-cluster-based computing • interest and ability to work on team-based projects Start date: Flexible between June and October 2020 To apply: send an email including your CV, research statement, and cover letter to mudrikli(a)tauex.tau.ac.il and mpitts(a)reed.edu by March 30th, 2020

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PhD Position in Computational Neuroscience, University of Edinburgh
by Chadwick, Angus Feb. 12, 2020

Feb. 12, 2020

Applications are invited for a fully-funded PhD studentship in Computational Neuroscience with Dr. Angus Chadwick at the Institute for Adaptive and Neural Computation in the School of Informatics, University of Edinburgh, commencing September 2020 or later. Exceptional applicants interested in a September 2021 start may also apply. Students should hold, or be close to completion of, an undergraduate or masters degree in physics, mathematics, computer science, engineering, or similar, and be interested in applying their analytical skills to tackle problems in neuroscience. Highly motivated students with other backgrounds may also be considered. The newly-formed Chadwick group focuses on the dynamics of neural populations underlying visual perception and spatial navigation. We use a combination of approaches, including 1) top-down modelling of neural circuit function guided by machine learning and artificial intelligence solutions 2) bottom-up analysis and simulation of neuronal network dynamics, and 3) statistical modelling of large-scale neural recordings. Our long-term goal is to develop a unified theory of the neural circuit computations supporting visual and spatial processing which spans these levels of analysis. We collaborate closely with a number of experimental neuroscience laboratories both in Edinburgh and further afield. Edinburgh is a vibrant and international city with a large student population, and has been voted as “best place to live in Britain”. The School of Informatics maintains an internationally-leading research environment in Computational Neuroscience, Machine Learning and Robotics, with close links to the Centre for Discovery Brain Sciences and the School of Philosophy, Psychology and Language Sciences. Applicants should email Dr. Angus Chadwick directly at angus.chadwick(a)ucl.ac.uk with their CV and a brief statement of interest, or for informal enquiries and discussion. Applications will be considered until the position is filled.

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International Brain Lab now hiring data scientists!
by Hannah M Bayer Feb. 11, 2020

Feb. 11, 2020

The International Brain Laboratory (https://www.internationalbrainlab.com/) is seeking 3 data scientists, who will play key roles in a large-scale international collaboration in brain research. The International Brain Lab combines the efforts of approximately 50 scientists in 20 laboratories toward understanding the brain-wide basis of a complex behavior. The project will involve recording the activity of millions of neurons in the working brain and building mathematical models of the resulting data. The data sets this project will produce are vast and complex, including physiological recordings, behavioural measurements, and video, all of which must be standardized into common formats, integrated into a single database, and subjected to quality control. These core positions will support both experimental and theoretical work through the entire lifecycle of data, including acquisition, analysis, modeling and dissemination. For more details about the positions, please check out: https://bit.ly/2OLwWwq or https://www.internationalbrainlab.com/opportunities Please address all inquiries about these positions to info+careers(a)internationalbrainlab.org

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