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

Recruitment of postdoctoral researchers and PhD students in computational brain science, Yonsei University College of Medicine
by Jiyoung Kang Dec. 9, 2019

Dec. 9, 2019

Dear all, It is our pleasure to announce an exciting opportunity for post-doc (or any other research) positions at Center for Systems and Translational Brain Science, Yonsei University, Republic of Korea (P.I. Professor Hae-Jeong Park). We develop computational methods to explore brain dynamics at various levels (from neuron to behavior), and seek for highly motivated candidates who find interest in computational neuroscience. The center specializes in the following domains: - Computational modeling based on dynamic causal modelling of the neural circuit observed in vitro and in vivo animal and human data (CaI, VSDI, LFP, M/EEG, BOLD). - Computational and systems neuroscience for the network controllability - Computational modeling of human behaviors We have neuroimaging facility of 3T fMRI, PET, EEG-fMRI, MEG, TMS+(navigation). Our research team is composed of multidisciplinary researchers from biophysics, biomedical engineering and cognitive science with strong clinical support. For details, please see the following web link: http://neuroimage.yonsei.ac.kr. If you have any questions, please contact Dr. Jiyoung Kang (jykang(a)yuhs.ac) Best regards Jiyoung Kang Center for Systems and Translational Brain Science Department of Nuclear Medicine, Radiology, Psychiatry, Department of Cognitive Science, Yonsei University College of Medicine, Seoul, Korea

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PhD Opening on large-scale dynamics of functional networks and information routing (@Aix-Marseille University)
by BATTAGLIA Demian Dec. 9, 2019

Dec. 9, 2019

We are recruiting one PhD fellow at the Institute for Systems Neuroscience at Aix-Marseille University. The student will work within Dr. Demian Battaglia’s group (theoretical neuroscientist), in strict interaction with other researchers at Aix-Marseille University (Andrea Brovelli, systems and cognitive neuroscientist; Alain Barrat, complex networks physicist). The project will delve with the analysis of multi-frequency dynamic brain networks in large-scale electrophysiological recordings. Brain regions interact between them in a highly dynamic manner even to perform very simple tasks, preventing too simplistic attempts of description. Flexibly changing patterns of information exchange and integration can be tracked using novel information theoretical and time-series analyses tools and generating directed multi-layer temporal networks representations of the data. In the framework of this project, a variety of different large-scale electrophysiological datasets (from rodents to non-human primates and humans), will be characterized based on complex network analyses tools that, initially forged in statistical physics, have not yet been adapted to be compliant with neural datasets, although they provide a natural language to describe the complex “life” of cell assemblies and transiently integrated coalitions of brain regions. The PhD fellow will characterize how spatio-spectro-temporal network patterns correlate or predict behavior and cognitive performance (e.g. in working memory or spatial navigation tasks) and, potentially, how these patterns are altered in specific animal pathology models (AD, ALS…). Network analyses of empirical data may be complemented by the design of connectome-based computational models of multi-scale oscillations, to reverse engineer physiological mechanisms (e.g. alterations of excitability) that may underpin generalized functional connectivity changes, in control or pathological conditions. This project is one of the “ESR” (Early Stage Researcher) positions opening within the Marie Skłodowska-Curie Innovative Training Network (ITN) project “i-Conn” funded by the European Commission, under their H2020 program. Such prestige program offers ideal conditions to the successful candidate such as: a salary well superior to the national average of ~1.9k euros monthly (plus family allowance when applies), net after taxes, with full social security coverage; and generous grant money for training and traveling to conferences. Through the ITN project activities, the PhD fellow will have the opportunity to come in contact with leading research groups in the UK, Germany, Czech Republic, Austria and Cyprus adopting network science techniques in a wide variety of disciplines, including neuroscience, but also socio-economics, geography, astronomy, etc. At Aix-Marseille University, the PhD fellow will integrate the second largest neuroscience community in France in a dynamic university with emphasis on interdisciplinary approaches. The PhD fellow will profit of the high-level training opportunities provided by the local “NeuroSchool” (https://neuro-marseille.org/en) an excellence PhD program in clinical and integrative neuroscience, as well as by convergence institutes as the Turing Center for Living Systems (http://centuri-livingsystems.org) In addition, Marseille is a vibrant multi-cultural city located in the beautiful natural and cultural context of Southern France, at a few hours only by direct high-speed train from European cities as Paris, Barcelona, Brussels or Frankfurt. We seek for candidates with computational neuroscience, physics or computer science/machine learning background (ideally but not necessarily). The most important prerequisite is the willingness and skill to explore large-scale datasets. Previous experience in programming, computational modeling or network analyses is a plus. The working and training language is English. IMPORTANT! some strict eligibility requirements apply to be eligible as an Early Stage Researcher funded by Marie Skłodowska-Curie program: 1) The applicant should have — at the date of recruitment — less than 4 years of a research career, and not have a doctoral degree. The 4 years are measured from the date when they obtained the degree which would formally entitle them to embark on a PhD, either in the country where the degree was obtained or in the country where the PhD is provided. 2) Trans-national mobility: The applicant — at the date of recruitment— should not have resided in the country where the research training takes place for more than 12 months in the 3 years immediately prior to recruitment, and not have carried out their main activity (work ,studies, etc.) in that country. For refugees under the Geneva Convention (1951 Refugee Convention and the 1967 Protocol), the refugee procedure (i.e. before refugee status is conferred) will not be counted as ‘period of residence/activity in the country of the beneficiary’. To register your interest in applying for this position please, and to ask for any further information, please contact demian.battaglia(a)univ-amu.fr. To apply for this position, we require a copy of your CV, degree transcripts, motivation letter and the names and/or recommendation letters of 2 referees. Please include your master thesis as well and any publication you authored (included manuscripts at preprint or sufficiently advanced draft stages).

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Research Associate in the Open Source Brain project, University College London
by Gleeson, Padraig Dec. 9, 2019

Dec. 9, 2019

(Apologies for cross postings) The Silver lab (http://silverlab.org) at University College London is looking to hire a postdoc/research associate to work on a project to extend the functionality of the Open Source Brain platform (http://www.opensourcebrain.org, Gleeson et al. Neuron 2019) to support the sharing of standardised experimental neuroscience data alongside neuronal models. This will involve building web-based infrastructure and the curation and standardisation of neuroscience models (in NeuroML format) and data (in Neurodata Without Borders format). This will facilitate collaborative model development and model reuse by the community as well as enable interactive display and analysis of models and neuroscience data through the browser. A PhD in neuroscience, physics, computer science or a related field is required, as well as experience in computational neuroscience, neuroinformatics, or development of analysis pipelines for electrophysiology and imaging data. A strong foundation in computer programming, with strong competencies in data structures, algorithms and software design is essential, along with demonstrable knowledge of UNIX/Linux, experience of web development technologies and Python and/or JavaScript programming experience. The successful applicant will have the opportunity to fully participate in the academic activities related to this initiative including contributing to research and attending scientific conferences. Deadline for applications is 3rd Jan 2020. The post is funded for 2 years in the first instance. Full details can be found here<https://atsv7.wcn.co.uk/search_engine/jobs.cgi?owner=5041179&ownertype=fair…>. For informal enquiries, please contact p.gleeson(a)ucl.ac.uk<mailto:p.gleeson@ucl.ac.uk> ----------------------------------------------------- Padraig Gleeson Room 321, Anatomy Building Department of Neuroscience, Physiology& Pharmacology University College London Gower Street London WC1E 6BT United Kingdom +44 207 679 3214 p.gleeson(a)ucl.ac.uk<mailto:p.gleeson@ucl.ac.uk> -----------------------------------------------------

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Workshop on Modelling Consciousness
by Xerxes D. Arsiwalla Dec. 9, 2019

Dec. 9, 2019

Dear Computational Neuroscience Community, We would like to announce a workshop on formal approaches to consciousness studies: https://modelling-consciousness.org/ This workshop brings together researchers who have a deep interest in questions related to the scientific study of consciousness as well as background in formal research topics in order to discuss mathematical questions in the scientific study of consciousness and formal models of the mind-matter relation. The workshop takes place in a mountain cabin in the Austrian alps in Dorfgastein from March 21st to 28th, 2020. Unlike usual workshops and conferences, the focus is not placed upon presentation of recent results, but on creating an atmosphere that stimulates discussion of open questions and new ideas concerning models of consciousness. The workshop is aimed at researchers of any age who are interested in the problems discussed in contemporary consciousness studies. A background in mathematics, physics or other formal disciplines of sciences is appreciated. The deadline for applications is January 31st, 2020. Application details can be found on our website given above. Best wishes on behalf of the workshop organizing committee, Xerxes D. Arsiwalla (IBEC & Universitat Pompeu Fabra) Ian Durham (Saint Anselm College) Johannes Kleiner Giovanni Rabuffo (University of Aix-Marseille) Joanna Szczotka (University of Sussex & Jagiellonian University) Sean Tull (Cambridge Quantum Computing)

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PhD position in Computational and Mathematical Neuroscience: Drug Discovery
by Serafim Rodrigues Dec. 8, 2019

Dec. 8, 2019

*This position encourages students in Engineering, Mathematics, Physics (or Biophysics) or Computer Science to apply.* We are seeking students that are highly motivated to pursue a PhD project that interfaces several fields, including Neuroscience, Computer Science, Biophysics with the aim to screen new drugs against Alzheimer’s Disease. The project will employ advanced methods in computer science (e.g. machine learning, molecular simulations) and other advanced methods from mathematics and biophysics to develop drugs with high therapeutic efficacy against identified pathways in Alzheimer’s patients. The project will be developed at BCAM (Basque Centre for Applied Mathematics) in Bilbao in collaboration with several centres in France, Canada and Singapore. Candidate’s requirements: - Should have completed an MSc. - The following background knowledge are desirable - Programming. - Mathematics. - Biophysics. Interested students, please contact srodrigues(a)bcamath.org

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Fwd: PhD and postdoctoral positions, University of Utah
by Alla Borisyuk Dec. 6, 2019

Dec. 6, 2019

Postdoctoral and PhD student positions are available at the University of Utah (Salt Lake City, USA) in the Computational Neuroscience group of Dr. Alla Borisyuk. Dr Borisyuk is affiliated with both Department of Mathematics and the Neuroscience program. Depending on the background of the trainee the placement might be possible in either program. Current projects include: - A mutiscale study of the role of astrocytes in neural networks; - Elucidating the odor coding and connectivity in mammalian and insect olfactory systems. All projects are in collaboration with local experimental neuroscience labs. We have dynamic, active, student-centered and supportive environment, with a multitude of opportunities for trainees to get involved in. Outside of the academics - the outdoor recreational opportunities (National parks, skiing, hiking, climbing) all around us in Utah are unparalleled. Salt Lake City is the center of a metropolitan area with a population of approximately one million residents, has extensive arts and cultural activities, and has a major international airport with a Delta Airlines hub and direct flights to most U.S. cities and direct international flights to Paris, London, Amsterdam, and Mexico City. The area has received international recognition for its new light rail system, foodie culture, downtown renewal, and increasing diversity. For project and position details and other inquiries please contact Alla Borisyuk: borisyuk(a)math.utah.edu Screening of candidates is ongoing, do not delay with your application!

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Post-doctoral Researcher - Statistical machine learning of neural time-series data and mechanisms of network coordination
by Kirst, Christoph Dec. 6, 2019

Dec. 6, 2019

Dear computational neuroscience community, The Kirst lab at UCSF<https://neurograd.ucsf.edu/people/christoph-kirst-phd-ms-bs> and the Bouchard lab at LBNL/UC Berkeley<https://bouchardlab.lbl.gov/> are looking for a joint post-doctoral researcher to work at the interface of dynamical systems, statistical machine learning, and neural time-series data. The goal is to better understand mechanisms underlying flexible network coordination in the brain. This position will focus on developing and applying methods to analyze neurophysiological signals from diverse brain areas.The post-doc will advance the state of the art in analysis methods to characterize brain dynamics and understand distributed computations in diverse brains areas. State-space modeling approaches will be integrated with emerging unsupervised learning and supervised inference procedures. This position will include a strong collaboration with both basic and clinical neuroscience labs across UCSF, UC Berkeley, and LBNL. The position is located at the University of California, San Francisco (UCSF) and LawrenceBerkeley National Laboratory (LBNL), and is part of a broader collaborative effort between UCSF, LBNL, and UCB. This Bay Area collaboration combines UCSF's strong clinical and experimental neuroscience experience with in vivo cortical electrophysiology, UCB's expertise in theoretical neuroscience, statistical learning and data analysis, and LBNL's supercomputing and applied mathematics together with electronics and microfabrication.Successful applicants will have access to the full range of facilities andexpertise uniquely allowed by this collaboration. The position has significant flexibility and the lab is committed to the professional development of the members, making it valuable preparation for people who are interested in academic, industrial or entrepreneurial careers. The position has no mandatory teaching or administrative duties, but the successful candidate will take an active role in mentoring students and further developing the research program. Excellent (written and oral) communication skills in English are required. The start date is flexible but ideally would be in June of 2020. Compensation will be commensurate with relevant experience. UCSF has competitive benefits and is an equal opportunity employer. UCSF is located in the Bay Area, which is one of the fastest-growing neurobiology-neurotechnology centers in the United States. The Bay Area offers a wide range of opportunities for recreation, culture, and easy access to domestic and international transportation. Applicants should have aPh.D. (or equivalent degree) in a computational oriented field (e.g., physics, computer science, electrical engineering, data science, etc.,) and/or a track record of advanced data statistical analysis of neural time-series data. Applicants must be able to work in a collaborative, multi-disciplinary environment and exhibit good communication skills. Experience with scientific programing languages (e.g., C/C++,Python, Matlab) is also required. To apply, please submit a CV and three letters of reference to: christoph.kirst(a)ucsf.edu and kebouchard(a)lbl.gov Yours sincerely, Christoph Kirst and Kristofer Bouchard

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Ph.D. positions in Math Biology and Computational Neuroscience at NJIT
by Victor Matveev Dec. 6, 2019

Dec. 6, 2019

Dear all, The Department of Mathematical Sciences at New Jersey Institute of Technology (NJIT) is inviting candidates to apply to one of our doctoral program tracks: (1) Applied Mathematics or (2) Applied Probability & Statistics. The Department's research focus spans Mathematical Biology and Computational Neuroscience, Scientific Computing, Fluid Dynamics, Materials Science, Wave Propagation, Applied Analysis, Applied Probability & Statistics, including Biostatistics and Data Science. Teaching and research assistantships are available, and include a tuition waiver and a competitive stipend. Application target date is December 15, 2019 but ongoing review will continue until all available positions are filled. To apply, please visit our homepage: https://www.njit.edu/graduatestudies/department-mathematical-sciences/ For more information, please email us (math(a)njit.edu, CC to:misieg@njit.edu, matveev(a)njit.edu) PhD Program advertisement flyer is available at http://web.njit.edu/~matveev/NJIT_DMS_PhD_flyer.pdf Sincerely, -- Admissions Committee, Department of Mathematical Sciences, NJIT -- _____________________________________________ Victor Matveev, Professor Applied Math, Biophysics, Neuroscience Department of Mathematical Sciences Graduate Faculty, Dept of Biological Sciences New Jersey Institute of Technology Newark, NJ 07102-1982 Office: Cullimore Hall 616 E-mail: matveev(a)njit.edu http://web.njit.edu/~matveev/

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Groningen Spring School on Cognitive Modeling: March 30 to April 3, 2020
by Jelmer Borst Dec. 5, 2019

Dec. 5, 2019

Fifth Groningen Spring School on Cognitive Modeling – ACT-R, Nengo, PRIMs, error-driven learning, and dynamical systems. – Date: March 30 to April 3, 2020 Location: Groningen, the Netherlands Fee: € 250 (late fee after February 15 will be € 300) More information and registration: www.cognitive-modeling.com/springschool <http://www.cognitive-modeling.com/springschool> We are happy to announce the fifth Groningen Spring School on Cognitive Modeling (March 30 to April 3, 2020). This year, the Spring School will again cover four different modeling paradigms: ACT-R, Nengo, PRIMs, and error-driven learning. It thereby offers a unique opportunity to learn the relative strengths and weaknesses of these approaches. Moreover, this year we are offering a lecture series on dynamical systems, which should be interesting for anyone looking into modeling cognitive dynamics at some level of abstraction. We recommend this lecture series as an excellent combination with Nengo, for those interested in neuromorphic computing. The first day will provide an introduction to all five topics. From day two, spring school students will be asked to commit to one topic, for which they will attend lectures as well as tutorials. In addition, students can sign up for a second topic, for which they will attend lectures only. All students are invited to join a series of plenary research talks on the different paradigms. On the first day, spring school students are asked to introduce themselves and their research interests in a poster session. Registration is now open. For more information and registration, please see the website: www.cognitive-modeling.com/springschool <http://www.cognitive-modeling.com/springschool> Please feel free to forward the information to anyone who might be interested in the Spring School. We are looking forward to welcoming you in Groningen, The Spring School team ______________ ACT-R Teachers: Jelmer Borst, Maarten van der Velde, Stephen Jones, & Katja Mehlhorn (University of Groningen) Website: http://act-r.psy.cmu.edu <http://act-r.psy.cmu.edu/>. ACT-R is a high-level cognitive theory and simulation system for developing cognitive models for tasks that vary from simple reaction time experiments to driving a car, learning algebra, and air traffic control. ACT-R can be used to develop process models of a task at a symbolic level. Participants will follow a compressed five-day version of the traditional summer school curriculum. We will also cover the connection between ACT-R and fMRI. Nengo Teacher: Terry Stewart (University of Waterloo) Website: http://www.nengo.ca <http://www.nengo.ca/> Nengo is a toolkit for converting high-level cognitive theories into low-level spiking neuron implementations. In this way, aspects of model performance such as response accuracy and reaction times emerge as a consequence of neural parameters such as the neurotransmitter time constants. It has been used to model adaptive motor control, visual attention, serial list memory, reinforcement learning, Tower of Hanoi, and fluid intelligence. Participants will learn to construct these kinds of models, starting with generic tasks like representing values and positions, and ending with full production-like systems. There will also be special emphasis on extracting various forms of data out of a model, such that it can be compared to experimental data. PRIMs Teacher: Niels Taatgen (University of Groningen) Website: https://www.ai.rug.nl/~niels/prims/index.html <https://www.ai.rug.nl/~niels/prims/index.html> How do people handle and prioritize multiple tasks? How can we learn something in the context of one task, and partially benefit from it in another task? The goal of PRIMs is to cross the artificial boundary that most cognitive architectures have imposed on themselves by studying single tasks. It has mechanisms to model transfer of cognitive skills, and the competition between multiple goals. In the tutorial we will look at how PRIMs can model phenomena of cognitive transfer and cognitive training, and how multiple goals compete for priority in models of distraction. Error-driven learning Teachers: Jacolien van Rij and Dorothée Hoppe (University of Groningen) Error-driven learning (also called discrimination learning) allows to simulate the time course of learning. It is based on the Rescorla-Wagner model (Rescorla & Wagner, 1972) for animal cognition, which assumes that learning is driven by expectation error, instead of behaviorist association (Rescorla, 1988). The equations formulated by Rescorla and Wagner have been used to investigate different aspects of cognition, including language acquisition (e.g., Hsu, Chater, and Vitányi, 2011; St. Clair, Monaghan, and Ramscar, 2009), second language learning (Ellis, 2006), and reading of complex words (Baayen et al, 2011). Although error-driven learning can be applied for all domains in cognitive science, in this course we will focus on how it could be used for modeling language processing and language learning. Dynamical Systems: a Navigation Guide Teacher: Herbert Jaeger (University of Groningen) This lecture-series gives a broad overview over the zillions of formal models and methods invented by mathematicians and physicists for describing “dynamical systems”. Here is a list of covered items: Finite-state automata with and without input, deterministic and non-deterministic, probabilistic), hidden Markov models and partially observable Markov decision processes, cellular automata, dynamical Bayesian networks, iterated function systems, ordinary differential equations, stochastic differential equations, delay differential equations, partial differential equations, (neural) field equations, Takens’ theorem, the engineering view on “signals”, describing sequential data by grammars, Chomsky hierarchy, exponential and power-law long-range interactions, attractors, structural stability, bifurcations, phase transitions, topological dynamics, nonautonomous attractor concepts. In the lectures, I try to work out the underlying connecting lines between the “dots” listed above. -- Jelmer Borst Assistant Professor Model-Based & Computational Neuroscience University of Groningen, Bernoulli Institute, dept. of Artificial Intelligence http://www.jelmerborst.nl/

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Postdoctoral positions, Brown University (Truccolo Lab)
by Wilson Truccolo Dec. 3, 2019

Dec. 3, 2019

Applications for postdoctoral positions in Computational Neuroscience 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 theoretical and data-driven stochastic models of neuronal network dynamics, including applications to collective dynamics in normal neocortex, and propagation and control of epileptic seizures. Neural data consist of recordings of ensembles of single-neurons and high-density local field potentials obtained via multiple intracortical microelectrode arrays implanted in human and nonhuman primates. The ideal candidate will have a strong background in computational/theoretical neuroscience, and modeling of stochastic neural dynamics. Related publications can be found on the Truccolo lab website ( http://www.truccololab.com/) 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. Associate Professor of Neuroscience Department of Neuroscience & Carney Institute for Brain Science, Brown University Lab website: http://www.truccololab.com/

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