December 2019 - Comp-neuro - lists.cnsorg.org

PhD AND POSTDOC POSITIONS IN COMPUTATIONAL NEUROSCIENCE IN BASEL, SWITZERLAND
by Rava A. da Silveira 29 Dec '19

29 Dec '19

*Several DOCTORAL and POSTDOCTORAL openings in the lab of RAVA AZEREDO DA SILVEIRA at the IOB, University of Basel* We invite applications for several Ph.D. and postdoctoral positions at the IOB, University of Basel, in Switzerland. Research questions will be chosen from a broad range of topics in theoretical/computational neuroscience and cognitive science (see the description of the lab’s activity, below). Candidates with backgrounds in mathematics, statistics, artificial intelligence, physics, computer science, engineering, biology, and psychology are welcome. Experience with data analysis and proficiency with numerical methods, in addition to familiarity with neuroscience topics and mathematical and statistical methods, are desirable. Equally desirable are a spirit of intellectual adventure, eagerness, and drive. Doctoral and postdoctoral salaries will be highly competitive. *Deadline* For full consideration, please apply by 30 January 2020. *How to apply* Please send a letter of motivation, a statement of research interests limited to two pages, a curriculum vitae including a list of publications, and any relevant publications to rava(a)iob.ch, and arrange for three letters of recommendations to be sent to the same address. In all email correspondence, please include the mention “APPLICATION-BASEL-PHD” or “APPLICATION-BASEL-POSTDOC” in the subject header, otherwise the application will not be considered. *Description of the lab’s activity* Rava Azeredo da Silveira’s lab focuses on a range of topics in theoretical and computational neuroscience and cognitive science. These topics, however, are tied together through a central question: How does the brain represent and manipulate information? Among the more concrete approaches to this question, the lab analyses and models neural activity in circuits that can be identified, recorded from, and perturbed experimentally, such as visual neural circuits in the retina and the cortex. Establishing links between physiological specificity and the structure of neural activity yields an understanding of circuits as building blocks of cerebral information processing. On a more abstract level, the lab investigates the representation of information in populations of neurons, from a statistical and algorithmic -- rather than mechanistic -- point of view, through theories of coding and data analyses. These studies aim at understanding the statistical nature of high-dimensional neural activity in different conditions, and how this serves to encode and process information from the sensory world. In the context of cognitive studies, the lab investigates mental processes such as inference, learning, and decision-making, through both theoretical developments and behavioral experiments. A particular focus is the study of neural constraints and limitations and, further, their impact on mental processes. Neural limitations impinge on the structure and variability of mental representations, which in turn inform the cognitive algorithms that produce behavior. The lab explores the nature of neural limitations, mental representations, and cognitive algorithms, and their interrelations.

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PhD AND POSTDOC POSITIONS IN COMPUTATIONAL NEUROSCIENCE AT ENS, PARIS
by Rava A. da Silveira 29 Dec '19

29 Dec '19

*Several DOCTORAL and POSTDOCTORAL openings in the lab of RAVA AZEREDO DA SILVEIRA at the Ecole Normale Supérieure, Paris* We invite applications for several Ph.D. and postdoctoral positions at the Ecole Normale Supérieure, in Paris. Research questions will be chosen from a broad range of topics in theoretical/computational neuroscience and cognitive science (see the description of the lab’s activity, below). Candidates with backgrounds in mathematics, statistics, artificial intelligence, physics, computer science, engineering, biology, and psychology are welcome. Experience with data analysis and proficiency with numerical methods, in addition to familiarity with neuroscience topics and mathematical and statistical methods, are desirable. Equally desirable are a spirit of intellectual adventure, eagerness, and drive. Doctoral and postdoctoral salaries will be competitive, appreciably higher than standard French salaries. The ENS, together with a number of neighboring institutions (College de France, Institut Curie, ESPCI, Sorbonne Université, and Institut Pasteur), offers a rich scientific and intellectual environment, with a strong representation in computational neuroscience and related fields. *Deadline:* For full consideration, please apply by 30 January 2020. *How to apply:* Please send a letter of motivation, a statement of research interests limited to two pages, a curriculum vitae including a list of publications, and any relevant publications to rava(a)ens.fr, and arrange for three letters of recommendations to be sent to the same address. In all email correspondence, please include the mention “APPLICATION-PARIS-PHD” or “APPLICATION-PARIS-POSTDOC” in the subject header, otherwise the application will not be considered. *Description of the lab’s activity:* Rava Azeredo da Silveira’s lab focuses on a range of topics in theoretical and computational neuroscience and cognitive science. These topics, however, are tied together through a central question: How does the brain represent and manipulate information? Among the more concrete approaches to this question, the lab analyses and models neural activity in circuits that can be identified, recorded from, and perturbed experimentally, such as visual neural circuits in the retina and the cortex. Establishing links between physiological specificity and the structure of neural activity yields an understanding of circuits as building blocks of cerebral information processing. On a more abstract level, the lab investigates the representation of information in populations of neurons, from a statistical and algorithmic -- rather than mechanistic -- point of view, through theories of coding and data analyses. These studies aim at understanding the statistical nature of high-dimensional neural activity in different conditions, and how this serves to encode and process information from the sensory world. In the context of cognitive studies, the lab investigates mental processes such as inference, learning, and decision-making, through both theoretical developments and behavioral experiments. A particular focus is the study of neural constraints and limitations and, further, their impact on mental processes. Neural limitations impinge on the structure and variability of mental representations, which in turn inform the cognitive algorithms that produce behavior. The lab explores the nature of neural limitations, mental representations, and cognitive algorithms, and their interrelations.

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Postdoctoral Positions in Theoretical Neuroscience @ Higher School of Economics, Moscow Russia
by boris gutkin 28 Dec '19

28 Dec '19

Post-doctoral position in Theoretical Neuroscience DEADLINE 9 February More Information: https://iri.hse.ru/cognitive_neuroscience3 <https://iri.hse.ru/cognitive_neuroscience3> Application link: https://iri.hse.ru/polls/323647081.html The Higher School of Economics Centre for Cognition & Decision Making <https://www.hse.ru/en/cdm-centre/> of the Institute of Cognitive Neuroscience in Moscow, Russia, invites applications for postdoctoral research positions in computational and mathematical approaches to understanding neural function and cognition at Theoretical Neuroscience Group (TNG). Research interests of the TNG at the Centre for Cognition and Decision Making are wide ranging, carried out in collaboration with the experimental labs at the Center. Current research topics include computational psychiatry, computational neuroeconomics, information processing in neurons and circuits, as well as role of oscillations in cognition. The candidate will have the opportunity to further define and expand the Group’s research programme. We are seeking highly qualified and motivated candidate with backgrounds in quantitative disciplines: applied mathematics, physics, computer science or engineering. Knowledge of biology, neuroscience and ability to work with data is highly desired. Candidates will be trained in model building, analysis and will be offered advanced training in neuroscience and cognitive psychology. Candidates will have an opportunity to develop independent research projects and collaborations under the direction of the group leading scientists. The TNG is a structural part of the HSE’s Centre for Cognition & Decision Making <https://www.hse.ru/en/cdm-centre/> with ample collaboration opportunities within the Centre with other research groups, both within Russia and internationally. This new international group is tightly linked with the Group for Neural Theory at the Ecole Normale Superior <http://iec-lnc.ens.fr/group-for-neural-theory/?lang=en> in Paris, where research internships and visiting positions can be made available. Application Process Applications must be submitted online. Please provide a CV, a statement of research interest and a recent research paper submitted via an online application form. At least two letters of recommendation should be sent directly to the International Faculty Recruitment Office at fellowship(a)hse.ru <mailto:fellowship@hse.ru> before the application deadline. Please note that direct applications to the hiring department may not be reviewed. More information can be also obtained from boris.gutkin(a)hse.ru

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COSYNE 2020: Registration; Travel grants; Cosyne Tutorials
by Tomas Hromadka 28 Dec '19

28 Dec '19

==================================================== Computational and Systems Neuroscience 2020 (Cosyne) MAIN MEETING 27 February - 01 March 2020 Denver, Colorado WORKSHOPS 02 March - 03 March 2020 Breckenridge, Colorado www.cosyne.org ==================================================== IMPORTANT DATES Online registration is now open. Travel grant submission is now open. Travel grant application deadlines *31 December 2019, 11.59PM PST (Undergraduate Travel Grant)* 14 January 2020, 11.59PM PST (Other travel grants) ----------------------------------------------- TRAVEL GRANTS ----------------------------------------------- Applications are now open for travel grants to attend the conference. Each awardee will receive at least $500 to help offset the costs of travel, registration, and accommodations. Larger grants may be available to those traveling from outside North America. Special consideration is given to scientists who have not previously attended the meeting, under-represented minorities, students who are attending the meeting together with a mentor, undergraduate students, and authors of submitted Cosyne abstracts. We currently offer five travel grant programs for New Attendees, Presenters, Mentors, Undergraduates, and Childcare travel grants. For details on applying, see Cosyne.org -> Travel grants. ---------------------------------------------------- COSYNE TUTORIALS ---------------------------------------------------- Cosyne 2019 will host two tutorial sessions on 27 February 2020. For details on Cosyne tutorials please visit Cosyne.org -> Tutorials 20. Tutorial 1: Cosyne 2020 Tutorial session sponsored by the Simons Foundation Topic: Normative approaches to understanding neural coding and behavior Speaker: Ann Hermundstad Ann Hermundstad is a Group Leader in the Computation & Theory research core at Janelia Research Campus. She studies how the brain creates and uses adaptive sensorimotor representations to generate flexible behavior. Her lab uses a combination of theory, modeling, and data analysis to explore how neural circuits can do this efficiently and flexibly, and works in close collaboration with experimentalists to test these ideas in biological systems. We are recruiting TAs for the tutorial session. If interested, please see Cosyne.org -> Tutorials 20 for details on how to apply. Tutorial 2 Topic: Neurodata without Borders Tutorial NWB is a data standard for neurophysiology, providing neuroscientists with a common standard to share, archive, use, and build common analysis tools for neurophysiology data. Navigating the Allen Brain Observatory ---------------------------------------------------- BRIDGE TO INDEPENDENCE AWARD ---------------------------------------------------- The Simons Foundation Autism Research Initiative (SFARI) is invested in supporting the next generation of top autism researchers. The Bridge to Independence grant program promotes talented early-career scientists by facilitating their transition to research independence and providing grant funding at the start of their professorships (https://www.sfari.org/2018/06/15/bridge-to-independence-award-request-for-a…) ---------------------------------------------------- COSYNE ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The MAIN MEETING is single-track. A set of invited talks is selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. The WORKSHOPS feature in-depth discussion of current topics of interest, in a small group setting. For details on workshop proposals please see below or visit Cosyne.org -> Workshops. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, and computation with spiking networks. This year we would like to foster increased participation from experimental groups as well as computational ones. Please circulate widely and encourage your students and postdocs to apply. COSYNE INVITED SPEAKERS Matthew Botvinick (Deepmind/Princeton) Megan Carey (Champalimaud) John Cunningham (Columbia) Gul Dolen (Hopkins) Rainer Friedrich (FMI Basel) Sam Gershman (Harvard) Lisa Giocomo (Stanford) Christopher Harvey (Harvard) Mehrdad Jazayeri (MIT) Wei Ji Ma (NYU) Hendrikje Nienborg (Tuebingen/NIH) Linda Wilbrecht (Berkeley) Marta Zlatic (Janelia) ORGANIZING COMMITTEE General Chairs: Eugenia Chiappe (Champalimaud) and Christian Machens (Champalimaud) Program Chairs: Anne-Marie Oswald (U Pittsburgh) and Srdjan Ostojic (Ecole Normale Superieure Paris) Workshop Chairs: Catherine Hartley (NYU) and Blake Richards (McGill) Undergraduate Travel Chairs: Angela Langdon (Princeton) and Robert Wilson (U Arizona) Diversity Chairs: Eva Dyer (Georgia Tech, Emory) and Eric Shea-Brown (U Washington) Publicity Chair: Adam Calhoun (Princeton) Development Chair: Michael Long (NYU) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT meeting [at] cosyne.org ---------------------------------------------------- COSYNE MAILING LISTS ---------------------------------------------------- Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See Cosyne.org -> Mailing lists for details.

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PhD Studentship in Neural Data Science, Computational Neuromodulation and Metalearning
by Wong-Lin, Kongfatt 27 Dec '19

27 Dec '19

Applications are invited for a Ph.D. studentship in Neural Data Science, Computational Neuromodulation and Metalearning, tenable in the Faculty of Computing, Engineering and the Built Environment at Ulster University, UK. This PhD project is a collaboration between Ulster University and the University of Oxford (amongst other collaborators) on the computational modelling and theoretical development of neuromodulation in decision-making and learning. For more information, please refer to: https://www.ulster.ac.uk/doctoralcollege/find-a-phd/512105 The application process for the Ph.D. studentship is opened with a closing date for applications on the 7th February 2020. The computational and cognitive neuroscience research community at the Intelligent Systems Research Centre at Ulster University focuses on both fundamental brain and behavioural sciences, and their applications, including neuro-inspired AI, neural engineering and neurotechnology, and clinical neuroscience. The successful PhD candidate will be based at the Research Centre while interacting closely with collaborators at the University of Oxford and other international research institutes. If you wish to discuss your application or enquire more about this Ph.D. studentship, please contact: Dr. KongFatt Wong-Lin (k.wong-lin(a)ulster.ac.uk<mailto:k.wong-lin@ulster.ac.uk>). ------------------- Dr. KongFatt Wong-Lin Intelligent Systems Research Centre School of Computing, Engineering and Intelligent Systems Faculty of Computing, Engineering and the Built Environment Ulster University Magee Campus UK https://www.ulster.ac.uk/staff/k-wong-lin This email and any attachments are confidential and intended solely for the use of the addressee and may contain information which is covered by legal, professional or other privilege. If you have received this email in error please notify the system manager at postmaster(a)ulster.ac.uk and delete this email immediately. Any views or opinions expressed are solely those of the author and do not necessarily represent those of Ulster University. The University's computer systems may be monitored and communications carried out on them may be recorded to secure the effective operation of the system and for other lawful purposes. Ulster University does not guarantee that this email or any attachments are free from viruses or 100% secure. Unless expressly stated in the body of a separate attachment, the text of email is not intended to form a binding contract. Correspondence to and from the University may be subject to requests for disclosure by 3rd parties under relevant legislation. The Ulster University was founded by Royal Charter in 1984 and is registered with company number RC000726 and VAT registered number GB672390524.The primary contact address for Ulster University in Northern Ireland is Cromore Road, Coleraine, Co. Londonderry BT52 1SA

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Announcing Okinawa/OIST Computational Neuroscience Course 2020
by Erik De Schutter 23 Dec '19

23 Dec '19

OKINAWA/OIST COMPUTATIONAL NEUROSCIENCE COURSE 2020 Methods, Neurons, Networks and Behaviors June 29 to July 16, 2020 Okinawa Institute of Science and Technology Graduate University, Japan https://groups.oist.jp/ocnc The aim of the Okinawa/OIST Computational Neuroscience Course is to provide opportunities for young researchers with theoretical backgrounds to learn the latest advances in neuroscience, and for those with experimental backgrounds to have hands-on experience in computational modeling. We invite graduate students and postgraduate researchers to participate in the course, held from June 29th through July 16th, 2020 at an oceanfront seminar house of the Okinawa Institute of Science and Technology Graduate University. Applications are through the course web page (https://groups.oist.jp/ocnc) only; January 1 - February 2, 2020. Applicants will receive confirmation of acceptance in March. Like in preceding years, the 17th OCNC will be a comprehensive three-week course covering single neurons, networks, and behaviors with ample time for student projects. The first week will focus exclusively on methods with hands-on tutorials during the afternoons, while the second and third weeks will have lectures by international experts. The course has a strong hands-on component based on student proposed modeling or data analysis projects, which are further refined with the help of a dedicated tutor. Applicants are required to propose their project at the time of application. There is no tuition fee. The sponsor will provide lodging and meals during the course and provides partial travel support. We hope that this course will be a good opportunity for theoretical and experimental neuroscientists to meet each other and to explore the attractive nature and culture of Okinawa, the southernmost island prefecture of Japan. Invited faculty: • Michael Berry II (Princeton University, USA) • Tiago Branco (Sainsbury Wellcome Centre, London, UK) • Zenas C Chao (University of Kyoto, Japan) • Erik De Schutter (OIST) • Kenji Doya (OIST) • Gaute Einevoll (Norwegian University of Life Sciences, Norway) • Tomoki Fukai (OIST) • Boris Gutkin (Ecole Normale Supérieure, Paris, France) • Bernd Kuhn (OIST) • Devika Narain (Erasmus Medical Center, Rotterdam, Netherlands) • Alex Pouget (University of Geneva, Switzerland) • Ivan Soltesz (Stanford University, USA) • Saori C. Tanaka (ATR, Japan) • Tatjana Tchumatchenko (Max Planck Institute for Brain Research, Frankfur, Germany) • Marylka Yoe Uusisaari (OIST)

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NeuroBridges 2020 Summer School Announcement
by Ahmed El Hady 22 Dec '19

22 Dec '19

*/NeuroBridges 2020 Summer school , Cluny, France/* */( September 6th - September 17th, 2020)/* */ /* I would like to bring to your attention the NeuroBridges 2020 Summer School <http://decision-making-lab.com/NeuroBridges/neurobridges2020.html> <http://decision-making-lab.com/NeuroBridges/neurobridges2020.html> NeuroBridges <https://www.facebook.com/NeuroBridges/>is a one-of-a-kind series of scientific meetings in brain research, which brings together Mediterranean and Middle Eastern scientists, in order to promote international scientific cooperation in system and computational neuroscience. A major goal of this school is to serve as a bridge between experimental and theoretical neuroscientists, addressing system-level questions. This year the school will primarily focus on the neural basis and computational principles underlying decision making. *The forthcoming NeuroBridges 2020*will be a ten-day summer school. Students will attend lectures delivered by a group of leading neuroscientists, experimentalists as well as theoreticians, which will address the fundamental questions in the field of decision making. In addition to the lectures, the students will work in groups on small research projects. The school is intended for graduate students and postdocs, primarily (but not only) from the Middle East and the Mediterranean region either working in their home countries or abroad. We will consider applicants with some background in related fields in neuroscience or cognitive psychology. Through the online application system, you will be asked to provide personal details, academic background, a motivation letter that should include a paragraph about your quantitative skills and a CV. In addition, we request two recommendation letters. The school will take place between *September 6 and September 17, 2020* in Le Centre de Conferences Internationales de Cluny (CCIC) <http://www.ccic.eu/index.html>. Cluny is a small medieval town in Burgundy, France, located about 400km southeast of Paris (accessible by fast train, TGV). All costs of registration and accommodation will be covered by the organizers. A limited number of travel grants will also be available. *NeuroBridges* is co-organized by Ahmed El Hady <http://scholar.princeton.edu/ahmedelhady/home> (Princeton Neuroscience Institute, USA), Yonatan Loewenstein <http://elsc.huji.ac.il/loewenstein/home>(Hebrew University of Jerusalem, Israel) and David Hansel <https://neurophys.biomedicale.parisdescartes.fr/members/david-hansel/> (CNRS, Paris, France). Review of applications will end in May 2020. *2020 Faculty:* Carlos Brody (Princeton) <https://pni.princeton.edu/faculty/carlos-brody> Ahmed El Hady (Princeton) <http://scholar.princeton.edu/ahmedelhady/home> David Hansel (CNRS) <https://neurophys.biomedicale.parisdescartes.fr/members/david-hansel/> Ifat Levy (Yale) <https://medicine.yale.edu/profile/ifat_levy> Yonatan Loewenstein (Hebrew U.) <https://elsc.huji.ac.il/faculty-staff/yonatan-loewenstein> Najib Majaj (NYU) <https://www.researchgate.net/profile/Najib_Majaj> Mike Shadlen (Columbia U.) <https://neuroscience.columbia.edu/profile/michaelshadlen> Eyal Winter (Hebrew U.) <http://www.ma.huji.ac.il/%7Emseyal/> Yoram Yovell (Hadassah Hebrew U. Medical Center) <http://yovell.co.il/en/> The deadline for application is *April 1st, 2020 *and the following is the website including the link for the online application: http://decision-making-lab.com/NeuroBridges/neurobridges2020.html <http://decision-making-lab.com/NeuroBridges/neurobridges2019.html> <http://decision-making-lab.com/NeuroBridges/neurobridges2019.html> For more information, please contact neurobridges2020(a)gmail.com <mailto:neurobridges2018@gmail.com>.

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Call for Papers: Workshop on Machine Learning and Computational Intelligence in multi-omics and medical image analysis, 5-7 June, Greece
by Tiago Azevedo 22 Dec '19

22 Dec '19

Dear all, Below find the call for papers for the workshop "Machine Learning and Computational Intelligence in multi-omics and medical image analysis (MALCI_MUOMI 2020)". It will be held during the 2020 AIAI conference, collocated with EANN 2020, the 21st International Conference on engineering Applications of Neural Networks. This will be held 5-7 June 2020, Porto Carras Grand Resort, Halkidiki Greece. **Important Dates** Paper Submission Deadline: 29th of February 2020 Notification of Acceptance/Rejection: 22nd of March 2020 Camera Ready Submission/Registration: 2nd of April 2020 Early / Author registration by: 2nd of April 2020 Conference Dates: 5-7 June, 2020 **Link for submissions** http://www.aiai2020.eu/malci_muomi2020/#submission **Aim and scope** There is an increasing need for the application of Machine Learning (ML) and Computational Intelligence (CI) techniques, which can effectively perform image processing operations (such as segmentation, co-registration, classification, and dimensionality reduction), in the fields of neuroimaging and oncological imaging. Although the manual approach often remains the golden standard in some tasks (e.g., segmentation), ML can be exploited to automate and facilitate the work of researchers and clinicians. Frequently used techniques include Support Vector Machines (SVMs) for classification problems, graph-based methods, and Artificial Neural Networks (ANNs). More recently, deep ANNs have shown to be very successful in computer vision tasks owing to the ability to automatically extract hierarchical descriptive features from input images. It has also been used in the oncological and neuroimaging domains for automatic disease diagnosis, tissue segmentation, and even synthetic image generation. The main issue, however, remains the relative sample paucity of the typical imaging datasets that leads to a poor generalisation of the employed deep ANNs, considering the high number of required parameters. Consequently, parameter-efficient design paradigms, specifically tailored to medical applications, ought to be devised, also by exploiting CI-based techniques (e.g., neuroevolution). In this context, these advanced ML techniques can be suitably exploited to combine heterogeneous sources of information, allowing for multi-omics data integration. Such a kind of analyses may represent a significant step towards personalised medicine. Topics of interest include but are not limited to: · ML techniques for segmentation, co-registration, classification, or dimensionality reduction of medical images · Deep neural networks for medical image super-resolution, de-noising and synthesis · Deep Learning for neuroimaging and oncological imaging analysis · Integration of multi-omics data · Brain network analysis · Application of graph theory to MRI and functional MRI (fMRI) data · Application of ML methods for neurodegenerative disease studies · Computational modelling and analysis of neuroimaging · Methods of analysis for structural or functional connectivity · Development of new neuroimaging tools · Radiomic analyses for tumour phenotypes · Radiogenomics for intra- and inter-tumoural heterogeneity evaluation · Generative adversarial models for data augmentation and image super-resolution · CI methods for optimizing medical image analysis tasks **Workshop Organizing Committee** Tiago Azevedo – Department of Computer Science and Technology , University of Cambridge, Cambridge, (UK) Giovanna Maria Dimitri – Department of Computer Science and Technology , University of Cambridge, Cambridge (UK), Department of Medicine, University of Siena (Italy) Prof Pietro Liò – Department of Computer Science and Technology , University of Cambridge, Cambridge, (UK) Dr Leonardo Rundo – Department of Radiology, University of Cambridge, Cambridge (UK ) Simeon Spasov – Department of Computer Science and Technology , University of Cambridge, Cambridge (UK) Dr Andrea Tangherloni – Department of Haematology, University of Cambridge, Cambridge, (UK) Jin Zhu – Department of Computer Science and Technology , University of Cambridge, Cambridge, UK

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Carnegie Mellon - University of Pittsburgh Joint Summer Undergraduate Program in Computational Neuroscience
by Tai Sing Lee 21 Dec '19

21 Dec '19

Please encourage computationally-oriented undergraduates to apply to the Summer 2020 undergraduate program in computational neuroscience (uPNC) in Pittsburgh! Undergraduates interested in receiving research training in computational neuroscience are encouraged to apply to an NIH-sponsored summer program at the Center for the Neural Basis of Cognition (CNBC) in Pittsburgh, PA. The CNBC is a joint interdisciplinary program of Carnegie Mellon University and the University of Pittsburgh. Starting in late May or early June each year, a select group of talented undergraduates will embark on a 10-week residential program that provides intensive, mentored research experiences in computational and theoretical neuroscience. Admitted students will receive a stipend and university dormitory housing. The core of the program is the opportunity to carry out an individual mentored research project working closely with a faculty mentor. Other aspects of the scientific program include faculty research talks, student presentations and discussion of articles from the scientific literature, presentations on career options and scientific ethics, and a concluding symposium in which students present their research. This program is intended for students who wish to pursue a Ph.D. after graduation. Any undergraduate may apply, but we are especially interested in attracting students with strong quantitative backgrounds. Many of our trainees are from colleges and universities that do not have extensive research programs, but all must be United States citizens or permanent residents, must be enrolled at a 4-year accredited institution, and must be in their sophomore or junior year at the time of application. CNBC is dedicated to creating an inclusive and welcoming environment for all students and we encourage applications from women, under-represented minorities, and individuals with disabilities. Additional information and the application can be found here <http://www.cnbc.cmu.edu/training/undergraduate/summer-undergraduate-researc…>. A showcase of past years’ undergraduate research and program schedules is available: summer uPNC 2019 <http://www.cnbc.cmu.edu/training/undergraduate/summer-undergraduate-researc…>, summer uPNC 2018 <http://www.cnbc.cmu.edu/training/undergraduate/summer-undergraduate-researc…>, summer uPNC 2017 <http://www.cnbc.cmu.edu/training/undergraduate/summer-undergraduate-researc…> mentored research is also available. Please contact Dr. Linda Moya (lhmoya(a)cmu.edu <mailto:lhmoya@cmu.edu>) for further questions.

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PhD fellowship in joint processing of audio and EEG signals
by Kaare Mikkelsen 20 Dec '19

20 Dec '19

Applications are invited for a PhD fellowship within Deep learning for joint processing of audio and EEG signals. The aim of the project is to develop algorithms for enhancing hearing aid performance through integration with ear-EEG. The project will investigate deep neural networks for joint processing of brain and audio signals. Read more at: https://eng.au.dk/fileadmin/DJF/ENG/Billeder/ECE/CenterforEarEEG/PhDPositio… <https://eng.au.dk/forskning/forskningsprogrammer-og-centre/center-for-ear-e…> -------------------------------------------------------------------- Kaare Mikkelsen, PhD Phys. Department of Engineering Aarhus University --------------------------------------------------------------------

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