- Comp-neuro - lists.cnsorg.org

Postdoctoral fellow in Computational Neuroscience investigating mechanisms of sensorimotor integration.

by Ausborn,Jessica

Dr. Jessica Ausborn’s group at Drexel University College of Medicine, in the Department of Neurobiology & Anatomy has a postdoctoral position available for an exciting new research project involving computational models of sensorimotor integration based on neural and behavior data in Drosophila. The interdisciplinary collaboration with the experimental group of Dr. Katie von Reyn (Drexel School of Biomedical Engineering) will involve a variety of computational techniques including the development of biophysically detailed and more abstract mathematical models together with machine learning and data science techniques to identify and probe the algorithms computed in neuronal pathways that perform sensorimotor transformations. The Ausborn laboratory is part of an interdisciplinary group of Drexel’s Neuroengineering program that includes computational and experimental investigators. This collaborative, interdisciplinary environment enables us to probe biological systems in a way that would not be possible with either an exclusively experimental or computational approach. https://drexel.edu/medicine/about/departments/neurobiology-anatomy/research… More details on how to apply can be found here: https://careers.drexel.edu/en-us/job/495192/postdoctoral-researcher ----- Jessica Ausborn Assistant Professor Neurobiology and Anatomy College of Medicine Drexel University 2900 W Queen Lane Philadelphia, PA 19129

Nov. 19, 2020

PhD with Bristol Neural Computation Hub

by Cian O'Donnell

The Bristol Neural Computation Hub, University of Bristol, UK is looking to recruit to a number of EPSRC-funded PhD studentships for a Sept/Oct 2021 start: the research areas considered include Computational Neuroscience and Machine Learning. We have a vibrant Computational Neuroscience group with strong collaborative links with local and international groups working in experimental neuroscience, in machine learning and cognitive science. We have interesting projects to offer in our respective research areas: Laurence Aitchison (http://www.gatsby.ucl.ac.uk/~laurence/) gaussian processes and deep learning. Jeff Bowers (https://jeffbowers.blogs.bristol.ac.uk) deep learning as models of cognition. Conor Houghton (https://conorhoughton.github.io) information theory, decision making and affective state and linguistics. Nathan Lepora (http://lepora.com) robotics, neuroscience, biomimetics. Cian O’Donnell (https://odonnellgroup.github.io) synaptic plasticity, autism, statistical methods for neural data. Rui Ponte Costa (https://neuralml.github.io) credit assignment in cortical circuits. More details on the group here: https://bristolcnu.github.io/research/ Bristol is one of the top places to live and work in the UK and so we urge you to apply or to recommend this opportunity to suitable students. Anyone interested should contact one of us to discuss potential project and their application as early as possible; there are notes on the application process below; the final application would need to be submitted by 15th Jan 2021. All the best, Conor, Nathan, Cian, Rui, Laurence, and Jeff ___________ Information on the studentships: http://www.bristol.ac.uk/engineering/postgraduate/funding/sceem-studentships International students (including EU who haven’t lived in the UK) are very much eligible to apply but the process will be more competitive as only maximum 30% of the studentships are open for them. The remainder of these studentships are subject to a UK residency requirement: (https://epsrc.ukri.org/skills/students/help/eligibility/) Students should contact one of us before applying as you would need our nomination and also time to develop their project proposal with us. The selection itself goes through a two step process, students are first accepted as PhD students by the University and are then considered for funding within the School. Applicants should apply via http://www.bristol.ac.uk/study/postgraduate/apply/ and select "Computer Science PhD", ensuring they submit a short research proposal outlining the research question or area they intend to focus on and a CV by the deadline.

Nov. 19, 2020

Neural Engineering NER2021 call for papers

by Alberto Mazzoni

Dear friends, The deadline for the submission of 4-page papers to our bi-annual IEEEembs conference on Neural Engineering NER2021 is approaching! NER is the world’s gathering place for biomedical engineers, neuroscientists, and clinicians to share research and to exchange ideas and breakthrough advances in novel engineering tools for elucidating brain function and neuro technologies for the restoration and enhancement of impaired sensory, motor, and cognitive functions. The conference program will feature keynote speakers, invited talks, mini-symposia, and poster sessions. Please note that there will be a Special Session on Computer Models in Neuroengineering. All papers will be peer reviewed. All accepted one page and four page papers will appear in the Conference Program. Only four page papers will have the opportunity to be published in IEEE XPlore.Please submit yourpapers on #neurotechnology #bionics #robotics #prosthetics #neuroscience#machinelearning and more Information and complete call for papers available here: https://neuro.embs.org/2021/ Thanks, best and see you there! Alberto Mazzoni www.santannapisa.it/en/computational-neuroengineering-laboratory

Nov. 19, 2020

Online workshop series - Neural Control: From data to machines

by plan4act

We are pleased to announce that registration is now open for the remaining sessions of our ongoing workshop series *Neural Control: From data to machines* with weekly Zoom-sessions each Thursday morning at 10am (CET) throughout November and December. It's not too late to register for tomorrow's session (*Nov 19th*)! Topic: Movement disorders leave individuals unable to control parts of their bodies, creating a disconnect between their brain and the world around them. This workshop series looks at how neural activity can be mapped to control smart systems, producing desired movements on demand. To discuss the implied problems and solutions, we have brought together experts from the different involved scientific fields. Details and registration at: https://alexandria.physik3.uni-goettingen.de/cns-group/projects/webinars/ <https://alexandria.physik3.uni-goettingen.de/cns-group/projects/webinars/> Confirmed Speakers: * *Dario Farina* * *Silvestro Micera* * *Tonio Ball* * *Nick Ramsay* * *Juan Álvaro Gallego* * *Florentin Wörgötter* * *Alexander Gail* * *Christian Tetzlaff* * *Michael Fauth* * *Tomoki Fukai* * *Petra Ritter* * *Valerio Mante* * *Hans Scherberger* * *Gordon Cheng* * *Poramate Manoonpong* * *Jan-Matthias Braun* * *Eugenio Gaeta* * *Daniel Durstewitz* * *Yukie Nagai* Please forward to anyone who may be interested. Best, Florentin Wörgötter and Christian Tetzlaff

Nov. 18, 2020

Computational Neuralengineering Training Program at Georgia Tech/Emory

by Rozell, Christopher J

The Georgia Tech/Emory Computational Neuralengineering Training Program (CNTP) is a collaborative partnership with the mission of training the next generation of researchers at the intersection of computational neuroscience, data science and clinical neurophysiology. The CNTP is a training program supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) to address the opportunities provided by the explosion of tools for measurement and manipulation of nervous system function and the challenges posed by neurologic disorders. Trainees in CNTP program consists of PhD students with clear interest in quantitative training and either basic or clinical study of the brain, and who are pursuing studies in any of these degree programs: Biomedical Engineering (GT and Emory), Bioengineering (GT), Electrical and Computer Engineering (GT) or Machine Learning (GT) PhD programs. In addition to the benefits of being part of the broad computational neuroscience community in Atlanta, CNTP trainees have access to a new restricted course on Clinical Experience for Engineers, regular meetings with the cohort for rich discussions in technical and professional development topics, and an annual retreat with faculty and students for deeper dives into research discussions. Fellows in the CNTP receive two years of funding which supports a rotation program between labs in the first year. Fellow applications are solicited in the spring from applicants to the degree programs listed above. To be considered for the CNTP Fellowship, all you need to do is apply to a participating graduate program and have aligned interests expressed in your research statement. Scholars in the CNTP are full members of the community with access to all of the same programming (but without the fellowship funding). Scholar applications will be solicited in the summer from students joining labs in the upcoming fall. While there are low barriers to performing interdisciplinary research across departmental boundaries, admissions are handled separately by each degree program. Students interested in participating in the CNTP program should apply to the program that best fits their goals and interests. Application deadlines are listed below, along with the CNTP training faculty affiliated with each degree program. Please contact crozell(a)gatech.edu with questions. ***DEGREE PROGRAMS*** Biomedical Engineering (GT and Emory) DEADLINE: December 1 Application information: https://www.bme.gatech.edu/bme/grad-prospective-student-apply Bioengineering (GT) DEADLINE: Same as the home school selected during application Application information: https://bioengineering.gatech.edu/applying-bioengineering-program Electrical and Computer Engineering (GT) DEADLINE: December 16 Application information: https://www.ece.gatech.edu/graduate-admissions Machine Learning (GT) DEADLINE: Same as the home school selected during application Application information: http://ml.gatech.edu/phd/admissions ***CNTP Training faculty*** --Georgia Tech-- Garrett Stanley Chris Rozell Rob Butera Hannah Choi Tim Cope Constantin Dovrolis Eva Dyer Irfan Essa Ross Ethier Bilal Haider Hang Lu Susan Margulies Cassie Mitchell Machelle Pardue Peng Qiu Annabelle Singer --Emory University-- Lena Ting Michael Borich Gordon Berman Nick Boulis Gary Clifford Bob Gross Shawn Hochman, Dieter Jaeger Shella Keilholz Robert Liu Babak Mahmoodi Svetlana Miocinovich Ilya Nemenman Chethan Pandarinath Astrid Prinz Sam Sober Thomas Wichmann

Nov. 17, 2020

Fully-funded PhD Position in Cognitive Neuroscience

by Alireza Soltani

Fully-funded PhD Position in Cognitive Neuroscience The Cognitive and Affective Neuroscience Lab and the Computational and Cognitive Neuroscience Lab at Dartmouth have a joint, fully-funded PhD position for a motivated student to work on an exciting project on understanding how interactions between belief, expectation, and prior experience shape learning about reward and pain, process of belief formation, and how expectation or reward and pain influences perception and learning. The project is a collaboration between two labs and involves a combination of human experiments and computational modeling. A suitable candidate would have a strong background in cognitive and/or computational neuroscience, good computer programming skills, and a strong desire to understand neural mechanisms underlying cognition. Interested candidates should contact Alireza Soltani (Alireza.Soltani(a)dartmouth.edu) and/or Tor Wager (Tor.D.Wager(a)dartmouth.edu) To apply, please visit the PBS’s Graduate Admissions page <https://pbs.dartmouth.edu/menufeature/graduate/graduate-admissions> Relevant references: Soltani, Khorsand, Guo, Farashahi, Liu (2016). Neural Substrates of Cognitive Biases during Probabilistic Inference. Nature Communications, 7:11393 Jepma, Koban, van Doorn, Jones, Wager (2018). Behavioural and neural evidence for self-reinforcing expectancy effects on pain. Nature human behaviour, 2(11):838-55.

Nov. 17, 2020

[Journals] 1st CFP: Special Issue on "Theory of Mind in Humans and in Machines"

by Bogdan Ionut Cirstea

Dear colleagues, Apologies for cross-posting. Together with Prof. Fabio Cuzzolin (Oxford Brookes University, UK) and Prof. Barbara Jacquelyn Sahakian (University of Cambridge, UK), we are organizing a special issue (Frontiers Research Topic) on the emerging topic of "Theory of Mind in Humans and in Machines" under the "Frontiers in Artificial Intelligence" and "Frontiers in Computational Neuroscience" journals. We would like to invite you to contribute articles to the Research Topic. For more information on this special issue, please visit the website at https://www.frontiersin.org/research-topics/16802/theory-of-mind-in-humans-… . Papers may be submitted until the 3rd of April 2021. Submitted papers should not be under consideration for publication elsewhere. We also encourage authors to send a short abstract (via the platform) to ensure compliance with the topic and scope of the Frontiers journals as early as possible. The submission of abstracts is not mandatory and the deadline is the 4th of December 2020. Topics of interest include, but are not limited to, theoretical proposals, computational experiments, and case studies of: • Computational Theory of Mind • Learning from Demonstrations • Cognitive Models for Learning from Demonstration and Planning • Neuroscience-inspired models of Theory of Mind • Human-Robot Interaction • Cooperative Inverse Reinforcement Learning (assistance games) • Learning from Preferences If you intend to send an article to the special issue, please do let us know by hitting the "Participate" button in the web interface. If you have any questions or need any kind of assistance from us, please do not hesitate to let us know. On behalf of the topic editors, Bogdan-Ionut Cirstea Topic Editors: Prof. Fabio Cuzzolin, Oxford Brookes University, UK < fabio.cuzzolin(a)brookes.ac.uk> Prof. Barbara Jacquelyn Sahakian, University of Cambridge, UK < bjs1001(a)cam.ac.uk> Dr. Bogdan-Ionut Cirstea, Oxford Brookes University, UK < bcirstea(a)brookes.ac.uk>

Nov. 16, 2020

PhD and Postdoc Positions in Computational/Theoretical Neuroscience (Western University)

by Lyle Muller

The lab of Lyle Muller (http://mullerlab.ca) in the Department of Applied Mathematics and the Brain and Mind Institute at Western University (London, Ontario) has multiple PhD positions and one postdoctoral position in computational and theoretical neuroscience. NeuroNex Postdoctoral Scholar: This scientist will work with an international NeuroNex consortium<https://www.nxwm.io> studying the transcriptomic, cellular, and network basis of working memory. The project will incorporate analysis of multichannel neural data and computational models ranging from single neurons to spiking neural networks and machine learning algorithms. The researcher will work within a dynamic team and with data at multiple scales (transcriptomics, intracellular patch clamp, and extracellular spiking data). Joint PhD position with Julio Martinez-Trujillo<https://martinez-trujillo-uwo.ca>: This scientist will join a growing marmoset electrophysiology program in the Martinez-Trujillo lab, where multichannel arrays will record neural spiking activity at high spatial and temporal resolution during sensory and cognitive tasks. These multimodal experiments will be complemented by computational analyses and models collaboratively developed in the two labs. Joint PhD position with Wataru Inoue<https://www.schulich.uwo.ca/physpharm/people/faculty/Bio%20Pages/inoue_wata…>: This scientist will develop a real-time interface between recorded neurons and computational models of these single cells. The candidate will then use these “dynamic clamp” recordings to study how the properties of single cells are shaped by network activity and how network activity is in turn shaped by these properties. Research in this project will involve developing intracellular recording paradigms in conjunction with single neuron and spiking network models. Candidates interested in the lab’s research are additionally encouraged to contact the PI to discuss other projects of interest. Research in the lab utilizes a combination of large-scale numerical simulations and analytical approaches. Prior experience with scientific computing languages (MATLAB, Julia, or Python) and/or low-level programming (C/C++) is preferred. Prior experience with computational modeling, signal processing, or random graph theory is also preferred. Western University offers an excellent research environment and support. Graduate students can apply through the departments of Applied Mathematics or Neuroscience. Interested candidates (both graduate and postdoc) can write to lmuller2(a)uwo.ca<mailto:lmuller2@uwo.ca> with a CV to arrange an interview. Review of applications will begin on 15 December. BrainsCAN has an upcoming Graduate Studentship<https://brainscan.uwo.ca/programs/graduate_studentship_program/index.html> (deadline 4 January 2021) for highly talented candidates. Both our group and the University are deeply committed to fostering diversity in the sciences. Applications from underrepresented groups are strongly encouraged. BrainsCAN has an upcoming EDI Postdoctoral Special Call<https://brainscan.uwo.ca/programs/pdf_special_call/index.html> (deadline 4 December 2020), and any interested applicants can write the PI directly to discuss applications for this opportunity. -- Lyle Muller http://mullerlab.ca

Nov. 16, 2020

Postdoctoral Fellow/Research Associate Position in Computational Neuroscience and Biomechanical Modeling

by Danner,Simon

We are looking to fill a Postdoctoral Fellow/Research Associate position in Computational Neuroscience and Biomechanical Modeling at the Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA. Our group studies the spinal locomotor circuitry and its interactions with the musculoskeletal system and afferent feedback. The qualified postdoc will work on several collaborative, interdisciplinary, NIH-funded projects to uncover the connectivity and function of somatosensory afferents and various genetically or anatomically identified interneurons. The studies involve the development of computer models of mouse, rat, and cat biomechanics connected with models of the spinal locomotor circuitry. The successful candidate will closely collaborate with other computational and experimental neuroscientists: they will use experimental data to implement and refine the model, and use the model to derive predictions that will then be tested experimentally by our collaborators. The qualified candidate will benefit from joining a well-funded research group that works in a dynamic, collaborative and interdisciplinary environment. The highly collegial Danner lab is a member of the Neuroengineering Program, the Theoretical & Computational Neuroscience group, and the Spinal Cord Research Center within Drexel University College of Medicine’s Department of Neurobiology and Anatomy (http://drexel.edu/medicine/About/Departments/Neurobiology-Anatomy/) in Philadelphia, PA. The Department provides an outstanding scientific environment for multidisciplinary training. Interactions and collaborations between labs and between other departments are encouraged. More detailed information can be found here: https://careers.drexel.edu/en-us/job/495193/postdoctoral-researcher To apply, please email a current CV and contact information for 3 references to smd395(a)drexel.edu<mailto:smd395@drexel.edu>. The position will remain posted until filled. -- Simon M. Danner Assistant Professor Neurobiology and Anatomy College of Medicine Drexel University 2900 W Queen Lane Philadelphia, PA 19129

Nov. 16, 2020

Special Research topic in Frontiers of Neuroscience: “Symmetry as a Guiding Principle in Understanding Neural Information Processing.”

by Benedetta Franceschiello

*S**pecial Research topic in Frontiers of Neuroscience. Guest editors: T. Poggio (MIT),F. Anselmi (BCM), A. Patel (BCM), A. Tacchetti (Deep mind)* *Title: *“Symmetry as a Guiding Principle in Understanding Neural Information Processing.” Researchers are invited to submit papers for this special edition. For more information, or to submit a manuscript, please visit URL: https://www.frontiersin.org/research-topics/15343/symmetry-as-a-guiding-pri… Submission deadline: April 13, 2021 The aim of this Research Topic is to cover promising, recent, and novel research trends regarding on the role of symmetry in shaping the learning/ information processing and neuronal organization in the brain, within a theoretical and computational perspective. Areas to be covered in this Research Topic may include, but are not limited to: - New architectures beyond convolutional networks: biologically plausible sensory representations that are simultaneously selective for object identity and invariant to nuisance variation (including but not limited to group transformations, beyond translations) in mammalian cortex. - Sample complexity and invariant representations: is the brain using symmetries to perform efficient computation? - Variants of common plasticity rules or new class of rules that incorporate sensory data symmetries: how can the brain discover data symmetries and learn to represent sensory input in an invariant way? - Role of time continuity, crucial in the sensory experience, in defining classes of symmetries (implicit unsupervised labelling For questions, please contact Prof. Fabio Anselmi via email: Fabio.Anselmi(a)bcm.edu

Nov. 16, 2020