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PhD position in computational neuroscience. 'Identification of Metastable Cortical Dynamics Underlying Cognitive Decisions'. Bournemouth University-IDIBAPS

by Emili Balaguer-Ballester

PhD position in computational neuroscience. 'Identification of Metastable Cortical Dynamics Underlying Cognitive Decisions'. Bournemouth University-IDIBAPS. A PhD position is available in 3-years fully-funded project "Identification of Metastable Cortical Dynamics Underlying Cognitive Decisions"; based at Bournemouth University (UK) and at the Biomedical Research Institute August Pi I Sunyer (IDIBAPS, http://www.idibaps.org/en_index.htm, University of Barcelona, Spain). Do we have analysis tools for a reliable identification of the dynamical processes underlying decision-making? This is a fundamental question, touching the very basics of our understanding of neural computation and hence one of the most exciting topics in neuroscience. However, to reconstruct in detail neural dynamics generating cognitive decisions is a major challenge for current methodologies. This would be a highly significant advance; for instance the identification of stable dynamical patterns of activity in hippocampus deserved to win the last Nobel Prize. The aim of the project is to develop innovative approaches designed for the identification of metastable dynamics underlying cognitive decisions. We aim for the fusion of statistical learning approaches to pattern discovery with methods for identifying neural attractor dynamics and neurocomputational modelling. The novel approach will reconstruct neural dynamics during tasks specifically designed at Sanchez-Vives Lab in rodents and in human subjects at the Bournemouth EEG lab. The training possibilities that this interdisciplinary project offers are multiple and relevant in building-up a high-profile as a neuroscientist. The student will benefit from the vibrant scientific environment of neural computation and neurosciences at BU and at the cortical networks lab; embedded in the renowned systems neuroscience network in Barcelona. Applicants holding a degree in Physics, Computer Science, Engineering, Mathematics or similar disciplines are welcome. Interest or previous training in neuroscience and machine learning, as well master qualifications in these subjects, laboratory experience and a strong mathematical background would be very welcome. The researcher would be based at the Faculty of Science, Bournemouth University, and work with Dr Balaguer-Ballester at the Computational Neuroscience laboratory (http://dec.bournemouth.ac.uk/staff/ebb) and would spend prolonged periods of time in the Cortical Networks Lab (http://www.sanchez-vives.org/ IDIBAPS, Barcelona) led by Prof. Maria Victoria Sanchez-Vives; providing an outstanding opportunity to gain a diverse experience of both neuro-computational and experimental approaches. For more information and for applying please visit https://research.bournemouth.ac.uk/pgr/funded-phd-studentships-in-the-facul… For further details please do not hesitate to contact me: eb-ballester(a)bournemouth.ac.uk; twitter: @emilibalball . Kind regards Emili BU is a Disability Two Ticks Employer and has signed up to the Mindful Employer charter. Information about the accessibility of University buildings can be found on the BU DisabledGo webpages This email is intended only for the person to whom it is addressed and may contain confidential information. If you have received this email in error, please notify the sender and delete this email, which must not be copied, distributed or disclosed to any other person. Any views or opinions presented are solely those of the author and do not necessarily represent those of Bournemouth University or its subsidiary companies. Nor can any contract be formed on behalf of the University or its subsidiary companies via email.

Oct. 8, 2015

Postdoctoral positions in theoretical biophysics at Emory University

by Nemenman, Ilya

Dear Colleagues, We’re happy to announce that the we are in the process of hiring multiple postdoctoral scientists for the newly-formed theoretical biophysics cluster at Emory University. If you could forward the attached ad to anyone who might be interested, or suggest suitable candidates, it would be greatly appreciated. Sincerely, Gordon Berman Ilya Nemenman Daniel Weissman ---------------------- Postdoctoral Positions: Theoretical Biological Physics at Emory University Applications are invited for multiple Postdoctoral Scientist positions in the new theoretical biophysics cluster at Emory University. The groups of Professors Gordon Berman, Ilya Nemenman, and Daniel Weissman constitute the core of the cluster, and additional members include groups within the Departments of Physics, Biology, Chemistry, and Biomedical Engineering, amongst others across Emory. The cluster studies a wide range of questions at the interface of physics and biology, with particular focus on modeling and quantifying behavior, collective information processing in neural and cellular systems, and evolutionary dynamics. A successful applicant will have a PhD and a strong publication record in theoretical physics, quantitative biology, computational neuroscience, or a related field. We are particularly interested in candidates with a track record of scientific creativity and independent thinking. Review of applications will begin immediately and will continue until the positions are filled. Please send your CV, a brief description of your research experience and interests, and a list of three references to q-bio-jobs(a)listserv.emory.edu. <mailto:q-bio-jobs@listserv.emory.edu> Emory University is one of the world’s leading research universities, with top-ranked programs in Population Biology Ecology and Evolution, Computational Neuroscience, Biomedical Engineering, and Biophysics. The outstanding School of Medicine and Rollins School of Public Health and the nearby Georgia Institute of Technology provide ample opportunities for collaborations. The hired postdoctoral scientists will benefit from unique resources available at Emory, such as the Center for Disease Control, located on Emory Campus, and the Yerkes Primate Research Center. Emory is located within a leafy neighborhood in the heart of Atlanta, a major cultural center and transportation hub, which offers high quality of life. Emory University is an AA/EEO employer. ________________________________ This e-mail message (including any attachments) is for the sole use of the intended recipient(s) and may contain confidential and privileged information. If the reader of this message is not the intended recipient, you are hereby notified that any dissemination, distribution or copying of this message (including any attachments) is strictly prohibited. If you have received this message in error, please contact the sender by reply e-mail message and destroy all copies of the original message (including attachments).

Oct. 8, 2015

PhD opportunities in Computational Neuroscience

by Claudia Clopath

Computational Neuroscience Laboratory Headed by Dr. Claudia *Clopath* Department of Bioengineering Imperial College London -----------------Requirements:----------------- The Computational Neuroscience Laboratory, headed by Dr. Claudia Clopath, is looking for a talented PhD student, interested in working in the field of computational neuroscience, specifically addressing questions of *learning and memory*. The perfect candidate has a strong mathematical, physical or engineering background (or equivalent), and a keen interest in biological and neural systems. Demonstrated programming skills are a plus. -----------------Research topic:----------------- Learning and memory are among the most fascinating topic of neuroscience, yet our understanding of it is only at the beginning. Learning is thought to change the connections between the neurons in the brain, a process called *synaptic plasticity*. Using mathematical and computational tools, it is possible to model synaptic plasticity across different time scales, which helps understand how different types of memory are formed. The PhD candidate will be working to build those models of synaptic plasticity, and study the functional role of synaptic plasticity in artificial neural networks. They will have the opportunity to collaborate with experimental laboratories, which study connectivity changes and behavioural learning. Candidates should be EU nationals. ----------------- The lab:----------------- The Computational Neuroscience Laboratory is very young and dynamic, and publishes in prestigious journals, such as Nature and Science. It is part of the Department of Bioengineering, which conducts state-of-the-art multidisciplinary research in biomechanics, neuroscience and neurotechnology. The lab is at *Imperial College London*, the 3rd ranked university in Europe, is in the top 10 worldwide, and is located in the city centre of London. More information can be found at: http://www.bg.ic.ac.uk/research/c.clopath/lab/index.html <http://www.bg.ic.ac.uk/research/c.clopath/> ----------------- How to apply:----------------- Candidates should send a single pdf file, consisting of a 1-page motivation letter, CV (mentioning that they are EU nationals) to clopathlab.imperial(a)gmail.com, with the subject containing 'PHD2016'. In addition, candidates should organize two letters of references to be sent to clopathlab.imperial(a)gmail.com. The application *deadline is **Oct 25th* (both for the application as well as for the two letters of references). Skype Interviews will be held on the Oct 29th. ----------------- Funding:----------------- The candidate will apply to an Imperial College PhD scholarship. Deadline for funding application is on Nov 12. More information can be found at: <http://www3.imperial.ac.uk/researchstrategy/funding/phdscholarships> <http://www3.imperial.ac.uk/studentfinance/prospectivepgstudents/phdscholars…> http://www3.imperial.ac.uk/studentfinance/prospectivepgstudents/phdscholars…

Oct. 7, 2015

POSTDOCTORAL POSITIONS IN COMPUTATIONAL NEUROSCIENCE AT BROWN UNIVERSITY

by Wilson Truccolo

POSTDOCTORAL POSITIONS IN COMPUTATIONAL NEUROSCIENCE AT BROWN UNIVERSITY: Applications for NIH-funded post-doctoral positions are invited for the Laboratory of Dr. Wilson Truccolo in the Department of Neuroscience at Brown University, Providence, RI, USA. The positions are for the development of data-driven stochastic and biophysical models of multiscale neural dynamics in human epilepsy. Data consist of simultaneous intracortical microelectrode array recordings of ensembles of single neurons and local field potentials, as well as ECoGs, during seizure and non-seizure states in individuals with intractable epilepsy. The project involves a collaboration between the labs of Dr. Truccolo and Dr. Sydney Cash (Massachusetts General Hospital, Harvard Medical School, Boston). The ideal candidate will have a strong background in computational/theoretical neuroscience and modeling of stochastic neural dynamics. Related recent publications can be found on the Truccolo lab website ( http://www.truccololab.com/ <http://dl.dropbox.com/u/983891/Truccolo_home.htm>). Inquiries should be addressed to Dr. Truccolo (wilson_truccolo(a)brown.edu) Applications including a CV, statement of research interests, and the names and full contact details of three referees should be sent to wilson_truccolo(a)brown.edu. -- Wilson Truccolo, Ph.D. Pablo J. Salame '88 Goldman Sachs Assistant Professor of Computational Neuroscience Department of Neuroscience & Institute for Brain Science, Brown University Lab website: http://www.truccololab.com/

Oct. 7, 2015

PhD Position in Deep Learning & Visual Neuroscience

by Paul Zhutovsky

Hi there, we at EyeQuant, a visual neuroscience / machine learning startup based in Berlin have teamed up with a Marie Curie training network to offer a fully salaried PhD candidate position at the rapidly advancing intersection of Deep Learning, Computer Vision and Visual Neuroscience, starting as soon as possible. This is a really unique opportunity to obtain a PhD through a prestigious programme while working with and at a successful technology software startup, enabling you to simultaneously advance your career prospects both inside and outside of academia. Your supervisor and PI will be neuroscientist and EyeQuant co-founder Prof. Dr. Peter König, who is the Director of the Institute of Cognitive Science and Head of the Neurobiopsychology Lab at the University of Osnabrück, Germany. You will be based in EyeQuant’s Berlin HQ, with regular trips to our Lab in Osnabrück. You can find more details and next steps here: http://www.eyequant.com/#!/jobs#phd-candidate-research-engineer Please note that in order to be eligible for the MARIE SKŁODOWSKA-CURIE grant, you must not have carried out your main research activity for more than 12 months in Germany in the previous 36 months.

Oct. 7, 2015

Tenure Track Faculty Position in Theoretical Condensed Matter and Biological Physics

by Stepanyants, Armen

The Department of Physics at Northeastern University invites applications for an Assistant or Associate Professor level tenure track position in theoretical condensed matter and biological physics to begin Fall 2016. This is a broad search covering all forefront areas of theoretical and computational condensed matter and biological physics. Candidates are expected to teach effectively both undergraduate and graduate physics courses, and establish an independent externally funded research program. The successful applicant is expected to have a PhD in Physics, although closely related areas will also be considered. Northeastern University is an Equal Opportunity, Affirmative Action Educational Institution and Employer, Title IX University, and an E-Verify Employer. Applications from minorities, women and persons with disabilities are particularly welcome. Application materials submitted online at https://neu.peopleadmin.com/postings/38431 should include a cover letter, curriculum vitae, research and teaching statements, and names and e-mail addresses of four references. The deadline for receipt of all application materials, including the reference letters, is January 15, 2016. The position will, however, remain open until a suitable candidate is selected.

Oct. 6, 2015

COSYNE 2016: Abstract submission is open, Workshop proposal deadline on Oct 31

by Tomas Hromadka

==================================================== Computational and Systems Neuroscience 2016 (Cosyne) MAIN MEETING Feb 25 - Feb 28, 2016 Salt Lake City, Utah WORKSHOPS Feb 29 - Mar 01, 2016 Snowbird Ski Resort, Utah www.cosyne.org ==================================================== IMPORTANT DATES Abstract submission is now open! Abstract submission deadline: 13 November 2015 Workshop proposal deadline: 31 October 2015 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. MAIN MEETING The main meeting is single-track. A set of invited talks are selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. Cosyne topics include but are not limited to: 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. When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting, due to space constraints. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. WORKSHOPS The workshops feature in-depth discussion of current topics of interest, in a small group setting. The goal is to provide an informal forum for the discussion of important research questions and challenges. Controversial issues, open problems, comparisons of competing approaches, and alternative viewpoints are encouraged. The overarching goal of all workshops should be the integration of empirical and theoretical approaches, in an environment that fosters collegial discussion and debate. Preference will be given to proposals that differ substantially in content, scope, and/or approach from workshops of recent years (examples available at www.cosyne.org) Relevant topics include, but are not limited to: sensory processing; motor planning and control; functional neural circuits; motivation, reward and decision making; learning and memory; adaptation and plasticity; neural coding; neural circuitry and network models; and methods in computational or systems neuroscience. CONFIRMED SPEAKERS: Blaise Aguera y Arcas (Google) Marisa Carrasco (NYU) Edward Chang (UCSF) Greg DeAngelis (Rochester) Mark Goldman (UC Davis) Sonja Hofer (Basel) Richard Mooney (Duke) Mala Murthy (Princeton) Peggy Series (Edinburgh) Reza Shadmehr (Johns Hopkins) Paul Smolensky (Johns Hopkins) Leslie Vosshall (Rockefeller) Xiao-Jing Wang (NYU) ORGANIZING COMMITTEE: General Chairs: Maria Geffen (U Penn) and Konrad Körding (Northwestern) Program Chairs: Megan Carey (Champalimaud) and Emilio Salinas (Wake Forest) Workshop Chairs: Claudia Clopath (Imperial College) and Alfonso Renart (Champalimaud) Publicity Chair: Xaq Pitkow (Rice) EXECUTIVE COMMITTEE: Anne Churchland (CSHL) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT cosyne.meeting [at] gmail.com

Oct. 6, 2015

Postdoctoral Position in Robust Intelligence / Theoretical Neuroscience

by Stepanyants, Armen

The Center for Interdisciplinary Research on Complex Systems and the Department of Physics at Northeastern University, Boston, invite applicants for a postdoctoral position in Robust Intelligence / Theoretical Neuroscience to begin in the fall of 2015. The successful candidate will work on an AIR FORCE sponsored project to create a theoretical framework for the analysis of the effects of learning and robust memory storage on synaptic connectivity in local cortical networks. Applicants should have a Ph.D. in computational neuroscience, physics, mathematics, or related quantitative disciplines. Track record of experience in computational neuroscience, as well as excellent theoretical and computational skills are required. Knowledge of machine learning, replica/cavity theory from statistical physics, cortical neuroanatomy and connectivity is preferred. To apply, please send (1) a CV, including a list of publications, (2) a summary of prior research accomplishments, and (3) names and contact information of three reference providers by email to Prof. Armen Stepanyants, a.stepanyants(a)neu.edu<mailto:a.stepanyants@neu.edu>. The position is available immediately, and applications will be accepted until the position is filled. The initial appointment is for one year with the possibility of renewal on a yearly basis. Northeastern is an Equal Opportunity/Affirmative Action Title IX Employer. More information can be found at the Neurogeometry Lab website, www.neurogeometry.net<http://www.neurogeometry.net>. Armen Stepanyants Associate Professor Department of Physics and Center for Interdisciplinary Research on Complex Systems Northeastern University 110 Forsyth St., Boston, MA 02115 Phone: (617) 373-2944 Fax: (617) 373-2943 http://www.neurogeometry.net/

Oct. 5, 2015

PhD position in Zurich

by Jean-Pascal Pfister

Applications are invited for one PhD student position at the University of Zurich. The position is funded by a SystemsX grant from the Swiss National Science Foundation. The project is entitled "Baysian learning of quantal parameters at single synapse resolution", and involves both experimentation and theory. Most models of synaptic transmission assume that all synapses between two neurons are identical. However, there is experimental evidence for significant heterogeneity in synaptic transmission between synapses. The major goal of this project is the development of an approach that allows for quantification of functional synaptic parameters incorporating single synapse heterogeneity. Half of the project will be devoted to experiments (electrophysiological and optophysiological investigation of synaptic transmission at Drosophila synapses), while the second part will involve modeling (Bayesian learning). The PhD student will be co-supervised by Prof. Martin Müller (Institute of Molecular Life Sciences, University of Zurich) and by Prof. Jean-Pascal Pfister (Institute of Neuroinformatics, ETH and University of Zurich). Both institutes offer ideal environments for performing theory-driven experiments due to the presence of many theoretical and experimental labs. The candidate should hold a Master degree/Diplom in Physics, Biology, Neuroscience, Computational Neuroscience or a related field. She/he should have prior experience in an experimental lab, a very strong mathematical background, and good programming skills. The applicant should submit a CV, a statement of research interests, marks obtained for the Master/Diploma, and the abstract of the Master/Diploma thesis in electronic format to Jean-Pascal Pfister (jpfister(a)ini.uzh.ch <mailto:jpfister@ini.uzh.ch>) or Martin Müller (Martin.Mueller(a)imls.uzh.ch <mailto:Martin.Mueller@imls.uzh.ch>). In addition, two referees should directly send a letter of recommendation by email. The position is offered for a period of three years, starting on the 1st of January 2016. Salary scale is provided by the Swiss National Science Foundation (www.snf.ch <http://www.snf.ch/>). Deadline for application is the 30th of October 2015 or until the position is filled. +++ Martin Mueller SNSF Assistant Professor Institute of Molecular Life Sciences University of Zurich Y55-K78 Winterthurerstrasse 190 8057 Zurich Switzerland www.imls.uzh.ch/mueller.html <http://www.imls.uzh.ch/mueller.html> www.neuroscience.ethz.ch/research/molecular_cellular/mueller <http://www.neuroscience.ethz.ch/research/molecular_cellular/mueller> +++ Jean-Pascal Pfister SNSF Assistant Professor Theoretical Neuroscience Group Institute of Neuroinformatics University of Zurich and ETH Zurich Winterthurerstrasse 190 8057 Zurich, Switzerland www.ini.uzh.ch/~jpfister <http://www.ini.uzh.ch/~jpfister> www.neuroscience.ethz.ch/research/computation_modeling/pfister <http://www.neuroscience.ethz.ch/research/computation_modeling/pfister>

Oct. 5, 2015

NIPS Workshop on Modelling and Inference for Dynamics on Complex Interaction Networks

by Yasser Roudi

We invite contributions to the workshop on Modelling and Inference for Dynamics on Complex Interaction Networks Friday 11 December 2015 Palais des Congrès de Montréal, Montréal, Canada Submissions of both contributed talks and posters are welcome. Please email an abstract of up to 1 page (PDF preferred) to peter....(a)kcl.ac.uk <> by 30 October 2015 and indicate your preference for talk or poster. We will get back to you with decisions on acceptance of submissions by mid-November. Further information on the workshop theme, invited speakers etc can be found below or at http://www.netadis.eu/ <http://www.netadis.eu/> (go to "NIPS 2015" tab). Please distribute to any researchers that might be interested in participating. Many thanks, Manfred Opper, Yasser Roudi and Peter Sollich --------------------------------------------- INVITED SPEAKERS and indicative topics • Jose Bento Ayres Pereira, Boston College – learning networks of stochastic differential equations • Mathias Bethge, MPI Tübingen – dynamics of generalized linear models • Alfredo Braunstein, Polictecnico di Torino – inference problems for irreversible stochastic epidemic models • Ramon Grima, University of Edinburgh – approximate solutions of Fokker-Planck equations, Feynman system size expansion • Andrea Montanari, Stanford – to be confirmed • Federico Ricci-Tersenghi, “La Sapienza” University, Roma – cross-correlations to infer delay structure then interactions • Graham Taylor, University of Guelph – deep learning in dynamical networks ORGANIZERS Prof Manfred Opper (Technische Universitaet Berlin, Germany), Prof Yasser Roudi (NTNU, Trondheim, Norway), Prof Peter Sollich (King’s College London, UK) CONTACT Prof Peter Sollich: peter....(a)kcl.ac.uk <> ABSTRACT Inference and learning on large graphical models, i.e. large systems of simple probabilistic units linked by a complex network of interactions, is a classical topic in machine learning. Such systems are also an active research topic in the field of statistical physics. The main interaction between statistical physics and machine has so far been in the area of analysing data sets without explicit temporal structure. Here methods of equilibrium statistical physics, developed for studying Boltzmann distributions on networks of nodes with e.g. pairwise interactions, are closely related to graphical model inference techniques; accordingly there has been much cross-fertilization leading to both conceptual insights and more efficient algorithms. Models can be learned from recorded experimental or other empirical data, but even when samples come from e.g. a time series this aspect of the data is typically ignored. More recently, interest has shifted towards dynamical models. This shift has occurred for two main reasons: * Most of the interesting systems for which statistical analysis techniques are required, e.g. networks of biological neurons, gene regulatory networks, protein-protein interaction networks, stock markets, exhibit very rich temporal or spatiotemporal dynamics; if this is ignored by focusing on stationary distributions alone this can lead to the loss of a significant amount of interesting information and possibly even qualitatively wrong conclusions. * Current technological breakthroughs in collecting data from the complex systems referred to above are yielding ever increasing temporal resolution. This in turn allows in depth analyses of the fundamental temporal aspects of the function of the system, if combined with strong theoretical methods. It is widely accepted that these dynamical aspects are crucial for understanding the function of biological and financial systems, warranting the development of techniques for studying them. In the past, the fields of machine learning and statistical physics have cross-fertilised each other significantly. E.g. the establishment of the relation between loopy belief propagation, message passing algorithms and the Bethe free energy formulation has stimulated a large amount of research in approximation techniques for inference and the corresponding equilibrium analysis of disordered systems in statistical physics. It is the goal of the proposed workshop to bring together researchers from the fields of machine learning and statistical physics in order to discuss the new challenges originating from dynamical data. Such data are modelled using a variety of approaches such as dynamic belief networks, continuous time analogues of these – as often used for disordered spin systems in statistical physics –, coupled stochastic differential equations for continuous random variables etc. The workshop will provide a forum for exploring possible synergies between the inference and learning approaches developed for the various models. The experience from joint advances in the equilibrium domain suggests that there is much unexplored scope for progress on dynamical data. Possible topics to be addressed will be: Inference on state dynamics: – efficient approximation of dynamics on a given network, filtering, smoothing – inference with hidden nodes – existing methods including dynamical belief propagation & expectation propagation, variational approximations, mean-field and Plefka approximations; relations between these, advantages, drawbacks – alternative approaches Learning model/network parameters: – with/without hidden nodes Learning network structure: – going beyond correlation information

Oct. 5, 2015