- Comp-neuro - lists.cnsorg.org

PhD position in Computational and Mathematical Neuroscience: Drug Discovery

by Serafim Rodrigues

*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

Dec. 8, 2019

Fwd: PhD and postdoctoral positions, University of Utah

by Alla Borisyuk

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!

Dec. 6, 2019

Post-doctoral Researcher - Statistical machine learning of neural time-series data and mechanisms of network coordination

by Kirst, Christoph

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

Dec. 6, 2019

Ph.D. positions in Math Biology and Computational Neuroscience at NJIT

by Victor Matveev

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/

Dec. 6, 2019

Groningen Spring School on Cognitive Modeling: March 30 to April 3, 2020

by Jelmer Borst

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/

Dec. 5, 2019

Postdoctoral positions, Brown University (Truccolo Lab)

by Wilson Truccolo

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/

Dec. 3, 2019

Neuroscience PhD Program, Tuebingen: deadline 15th Dec

by Peter Dayan

The Max Planck Institute for Biological Cybernetics and the University of Tübingen invite students from all over the world to apply for their interdisciplinary 5-year PhD program leading to a PhD in Neuroscience. Full funding will be available for top-ranked applicants. We are seeking talented, curious and open-minded young scientists with strong backgrounds in neuroscience, biomedical sciences, computational science, applied mathematics, statistics, artificial intelligence, or engineering. Successful candidates will possess a burning aspiration to shape the future of neuroscience and the ability to thrive in a fast-paced, interdisciplinary, environment. The application deadline is December 15, 2019. Please visit: https://www.kyb.tuebingen.mpg.de/phd-program for more details and information about applying. The PhD program is a collaboration between the Max Planck Institute for Biological Cybernetics and the University of Tübingen. It is closely affiliated with the renowned Graduate Training Centre of Neuroscience, the centerpiece of neuroscience training in Tübingen. Students (who should have been awarded a Bachelor's degree by September 2020) will receive a broad interdisciplinary training in neuroscience, including expert teaching by international renowned scientists and individual and intensive mentoring. Potential research topics cover a variety of fields in systems neuroscience, cognitive and behavioral neuroscience, computational neuroscience, translational and clinical neuroscience as well as cellular and molecular neuroscience. Teaching and research are conducted in English.

Dec. 3, 2019

Single Units and Human iEEG Meeting - April 1-3, 2020 - Birmingham UK

by MJ ter Wal

Dear colleagues, We are very happy to announce registration and abstract submissions are open for SUsHi 2020! The Single Units and Human iEEG Meeting (SUsHi), taking place in Birmingham, UK, from 1st – 3rd April 2020, will bring together Cognitive Neuroscientists working with human single unit and/or LFP recordings. The three day event will comprise of a small workshop followed by a two-day traditional conference, hosted at the University of Birmingham. SUsHi will bring together researchers who work with these rich and complex datasets, with the aim to discuss the appropriate methods for data analysis, hands-on training for researchers who are new to these methods, and a discussion of the latest scientific progress in the field. This three day event includes a spike sorting workshop for early career researchers (sold out), panel discussions, poster sessions and the chance to take part in a Method Challenge prior to the conference. We have exciting Keynote Presentations from Prof. Florian Mormann, Dr Leila Reddy, Dr Ueli Rutishauser and Prof. Rodrigo Quian Quiroga. You can *register *here: https://shop.bham.ac.uk/conferences-and-events/college-of-medical-dental-sc… submit *abstracts *here: https://memorybham.squarespace.com/abstract-submission and find out more about our *Method Challenge* here: https://memorybham.squarespace.com/method-challenge * * *Important deadlines:* 15th January – Abstract and Method Challenge Submissions 16th March – Registration Kind regards, Dr Simon Hanslmayr, Dr Bernhard Staresina and Dr Maria Wimber SUsHi Organisers SUsHi(a)contacts.bham.ac.uk https://memorybham.squarespace.com/sushi2020 <mailto:SUsHi@contacts.bham.ac.uk>

Dec. 2, 2019

Postdoctoral Fellowships at the Computational Brain Science group at Western University

by Jorn Diedrichsen

Postdoctoral Fellowships at the Computational Brain Science group at Western University The newly formed Computational Brain Sciences Group<https://brainscan.uwo.ca/research/cores/computational_core/index.html> at Western University offers postdoctoral positions through Western’s prestigious BrainsCAN postdoctoral fellowship program<https://brainscan.uwo.ca/research/cores/computational_core/postdoctoral_and…>. Applicants should have a PhD in a computational or neuroscience-related field. Candidates with expertise in both are strongly preferred. The successful applicant will play a key role in neuroimaging and computational investigations of human brain function. They will enjoy working as part of an interdisciplinary collaborative team and will join the Brain and Mind Institute<https://www.uwo.ca/bmi/> (BMI), which is one of the leading centres in cognitive neuroscience in Canada. The BMI hosts a full range of ultra-high field, research-dedicated MRI scanners and state-of-the-art research facilities for cognitive, behavioural, and neurophysiological testing. The applicant should contact one or more potential supervisors<https://brainscan.uwo.ca/research/cores/computational_core/affiliated_labs.…> with a cover letter, a detailed CV and 2-3 referees. Review of applicants will start on Dec 15, 2019. The deadline for submitting the final proposal is Feb 1st, 2020. In brief, applicants must be no more than 6 years post-PhD and the salaries are highly competitive (55-70K per year, CDN, with additional benefits). The proposed research should fit within the broad BrainsCAN remit, which covers research that addresses fundamental questions regarding how we learn, think, move, and communicate. Jörn Diedrichsen Western Research Chair Brain Mind Institute Department of Computer Science Department of Statistics Email: jdiedric(a)uwo.ca<mailto:jdiedric@uwo.ca> Tel: 1-519-661-2111 x86994

Dec. 2, 2019

Postdoc in computational neuroimaging

by Vuksanovic, Vesna

Dear List The following link contains details of a postdoc vacancy at University of Aberdeen in understanding of multi-modal MRI brain data to develop a network approach in understanding changes in brain structure and functions in patients with Alzheimer's disease: https://www.jobs.ac.uk/job/BWR950/research-fellow Please forward the link, if you know of some potential candidates. Many thanks, Vesna The University of Aberdeen is a charity registered in Scotland, No SC013683. Tha Oilthigh Obar Dheathain na charthannas clàraichte ann an Alba, Àir. SC013683.

Dec. 2, 2019