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PhD openings in computational neuroscience, cognitive science, and Mixed Reality
by Sergio Solinas 24 Oct '22

24 Oct '22

The Theoretical and Computational Neuroscience Laboratory of Paolo Enrico and Sergio Solinas invites applications for a *Doctoral Student* position at UNISS, University of Sassari, ITALY SARDINIA. Research questions span a range of topics in theoretical/computational neuroscience, cognitive science, EEG recordings involving data analysis, brain function theory, neural network simulations using NEURON or NEST and neural activity visualization using mixed reality approaches. This research project is inscribed within the EBRAINS-ITALY PNRR funding schema for Research Infrastructures. Candidates with backgrounds in one or more than one of the following fields are welcome to apply: mathematics, statistics, artificial intelligence, physics, computer science, engineering, biology, and psychology. Experience with data analysis, proficiency with numerical methods, and familiarity with neuroscience topics and mathematical and statistical methods are desirable. Equally desirable is a curiosity about brain function, a spirit of intellectual adventure, a good social attitude, and sharing and reuse of knowledge. The application will open soon. *Please write to both enrico(a)uniss.it <enrico(a)uniss.it> & smgsolinas(a)uniss.it <smgsolinas(a)uniss.it> for details and updates.* If you wish to apply, please send the following information in one single PDF: 1. a short letter of motivation; 2. statement of research interests, limited to two pages; 3. curriculum vitæ. In all email correspondence, please include the mention “APPLICATION-PHD” in the subject header. The University of Sassari <https://en.uniss.it/> was funded in 1562 and is an active research <https://en.uniss.it/research/research-centres> institution. The city of Sassari <http://turismosassari.it/en/explore/sassari-curiosities/item/535-sassari-on…>a located in the north of Sardinia <https://www.sardegnaturismo.it/en>. The climate <https://weatherspark.com/y/58783/Average-Weather-in-Sassari-Italy-Year-Round> is among the best you can find in Europe. The life cost is relatively cheap if compared to Italy's mainland. The island of Sardinia has national and international connection flights from its three airports: Alghero <https://www.aeroportodialghero.it/>, Olbia <https://www.geasar.it/>, and Cagliari <http://www.sogaer.it/it>.

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Funded PhD Scholarship in Developmental Neurorobotics at Sheffield Hallam University (UK)
by Di Nuovo, Alessandro 23 Oct '22

23 Oct '22

About the Project This scholarship will support the PhD candidate to carry out frontier research in Developmental Neurorobotics, a combination of Neuromorphic Computing and Cognitive Developmental Robotics. The PhD candidate will work with the Professor Alessandro Di Nuovo and his team, who have been awarded funding by the EPSRC for his research in the field. We are looking for an outstanding student to work with the team of a new EPSRC project. The research will pioneer the new developmental neuromorphic paradigm, which will be a synergic combination that will go beyond the limitations of the individual paradigms: neuromorphic computing will provide efficient brain-like resources able to process a more accurate representation of the real world, meanwhile developmental robotics will deliver the missing learning mechanisms for complex applications of neuromorphic spiking neural networks. The short-term objective is to demonstrate feasibility and lay the foundation of a biologically plausible framework to simulate the human-like learning process of numerical and abstract cognition, a fundamental characteristic of human intelligence. The team long-term goal is to create an artificial mind for robots that 'grows up' like a child's brain. This will be underpinned by neuromorphic computing which emulates the deep-lying architecture of the brain and will allow it to interpret and adapt to situations. As well as enabling the creation of robots with a human-like ability to reason, behave and interact the creation of an artificial mind will boost research in life sciences disciplines such as neuroscience by allowing researchers to run biologically realistic simulations to test theories. By simulating information on the inner workings of the brain that could not otherwise be detected, it could enhance our understanding of neurodevelopmental and learning disorders and lead to new treatments. Eligibility Information on entry requirements can be found here<https://www.findaphd.com/common/clickCount.aspx?theid=147190&type=184&DID=6…> The ideal candidate should have a Masters degree in Neuromorphic Computing, Computational Neuroscience, Machine Learning, or closely related disciplines in AI and Robotics, excellent programming skills and experience in interdisciplinary research. How to apply Your application should be emailed to industry-innovation-admissions(a)shu.ac.uk<javascript:void(0)> by the closing date of 31 October 2022. Any interested candidates must contact the lead academic, Prof. Alessandro Di Nuovo, a.dinuovo(a)shu.ac.uk<javascript:void(0)>, to discuss your application. The application should explain how the candidate knowledge, skills and experience are relevant to the project short and long-term objectives. Start date for studentship: 01/02/2023 Interviews are scheduled for: 11/11/2022 For information on how to apply please visit https://www.shu.ac.uk/research/degrees<https://www.findaphd.com/common/clickCount.aspx?theid=147190&type=184&DID=6…> ________________________________ Funding Notes The PhD studentship provides tuition fees at UK level and a maintenance bursary at the UK Research Councils' national minimum doctoral stipend rate (£17,668 for 2022/23). The scholarship is available for three years of full-time. ________________________________ References Di Nuovo, A., McClelland (2019). Developing the knowledge of number digits in a child-like robot. Nature Machine Intelligence, 1(12), 594-605. Di Nuovo, A., & Jay, T. (2019). Development of numerical cognition in children and artificial systems: a review of the current knowledge and proposals for multi-disciplinary research. Cognitive Computation and Systems, 1(1), 2-11. Di Nuovo, A., & Cangelosi, A. (2021). Abstract Concept Learning in Cognitive Robots. Current Robotics Reports, 2(1), 1-8. Roy, Jaiswal, Panda, (2019). Towards spike-based machine intelligence with neuromorphic computing. Nature, 575(7784), 607-617. Krichmar (2018). Neurorobotics-A Thriving Community and a Promising Pathway Toward Intelligent Cognitive Robots. Frontiers in Neurorobotics, Vol. 12, p. 42. Furber (2016). Large-scale neuromorphic computing systems. Journal of Neural Engineering, 13(5), 51001. Sengupta, et al. (2019). Going deeper in spiking neural networks: VGG and residual architectures. Frontiers in Neuroscience, 13, 95. Quax, D'Asaro,van Gerven, (2020). Adaptive time scales in recurrent neural networks. Scientific Reports, 10(1), 11360. Alessandro Di Nuovo, PhD Professor of Machine Intelligence College of Business, Technology and Engineering Sheffield Hallam University, United Kingdom Email: a.dinuovo(a)shu.ac.uk<mailto:a.dinuovo@shu.ac.uk>

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Faculty position in computational neuroscience/machine learning at Stony Brook University
by Giancarlo La Camera 22 Oct '22

22 Oct '22

Stony Brook University is currently running a faculty search for a computational neuroscientist. The position will be in the Department of Neurobiology and Behavior and will be filled at the Assistant or Associate Professor level. A competitive recruitment package will include state-funded salary and benefits, newly renovated lab space and competitive start-up funding. The ideal candidate is an outstanding scientist in theoretical neuroscience, neuro-AI or in statistics/machine learning approaches to investigate topical questions in neuroscience. Candidates from diverse and underrepresented backgrounds are especially encouraged to apply. The successful candidate will join a vibrant, collaborative and diverse group of neuroscientists at Stony Brook University and its affiliated institutions, and will actively contribute to the Department’s mission in research as well as undergraduate, graduate and medical student education. Applications should be submitted at the following URL: https://apply.interfolio.com/111422. Review of applications will begin by Nov 15th, 2022 and continue until the position is filled. -- Giancarlo La Camera <https://www.stonybrook.edu/commcms/neurobiology/people/faculty_Giancarlo_La…>, PhD Associate Professor of Neurobiology and Behavior Director, Center for Neural Circuit Dynamics <https://www.stonybrook.edu/cncd/> Stony Brook University

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Brain Criticality 2022 Hybrid Meeting - Deadline October 23rd for virtual registration
by BATTAGLIA Demian 21 Oct '22

21 Oct '22

*** LAST DAYS TO REGISTER FOR VIRTUAL PARTICIPATION AND SUBMIT VIRTUAL POSTER ABSTRACT*** We are happy to announce that the next conference on “Criticality in Neural Systems 2022: Collective Behavior, Synchronization, and Complexity” will take place at the Porter Neuroscience Research Center (National Institute of Health, Bethesda, MD, USA) from Nov. 7 – 9th, 2022 (shortly before the SFN Meeting, San Diego) The conference will be held in a hybrid format, both in presence at NIH Bethesda and via Zoom. Presentations by the invited speakers, with ample time for discussions, including with online participants, will be complemented by a poster session (in presence and online) and by a selection of contributed spotlight presentations. Keeping line with previous editions of the Brain Criticality conferences series, this conference will present the latest experimental and theoretical advancements in the study of critical phenomena in brain activity and their functional relevance. While preserving emphasis on criticality, this edition will feature as well communications about general collective behavior and dynamic complexity in the brain (and other biological systems). REGISTRATION IS OPEN AND FREE ON https://braincriticality.org/ Deadline for virtual registration: October 23rd Deadline for abstract submission (with spotlight oral preference): October 9th Deadline for abstract submission (poster only): October 23rd Confirmed Speakers Ad Aertsen (Freiburg, Germany) Dante Chialvo (Buenos Aires, Argentina) Karin Dahmen (Urbana-Champaign, IL) Irene Giardina (Rome, Italy) Michelle Girvan (College Park, MD) Moritz Helias (Jülich, Germany) Henrik Jensen (London, UK) Arvind Kumar (Stockholm, Sweden) Anna Levina (Tübingen, Germany) Klaus Linkenkaer-Hansen (Amsterdam, the Netherlands) Simona Olmi (Sesto Fiorentino, Italy) Orit Peleg (Boulder, CO) Pawel Romanczuk (Berlin, Germany) Woodrow Shew (Fayetteville, AR) James Shine (Sidney, Australia) Samir Suweis (Padova, Italy) Enzo Tagliazucchi (Buenos Aires, Argentina) Bradley Voytek (La Jolla, CA) Ralf Wessel (St Louis, MO) Changsong Zhou (Hong Kong, Popular Republic of China) Organizers Dietmar Plenz (Bethesda, MD) Lucilla de Arcangelis (Caserta, Italy) Miguel Angel Munoz (Granada, Spain) Mauro Copelli (Recife, Brazil) Demian Battaglia (Marseille & Strasbourg, France) For more information visit our website https://braincriticality.org/ or contact us over email.

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Computational Neuroscience and Computational Neurology
by André Fabio Kohn 20 Oct '22

20 Oct '22

Computational Neuroscience has shown a tremendous development in the last decades, and we think it is ripe to contribute substantially to computational neurology. In selected cases, large-scale and multi-scale models encompassing sensory receptors, neurons, muscles, bones, joints and other structures can be modeled to represent different degrees of dysfunction of a specific subsystem associated with a given neurological pathology. The model simulations can shed light to early signs of the disease (earlier detection than with current diagnosis techniques) and provide estimates of the progression of disease as a function of different treatment courses. We show in a recent paper published in the Journal of Neural Engineering [ https://iopscience.iop.org/article/10.1088/1741-2552/ac91f8/pdf] how neuropathies associated with Guillain-Barré Syndrome can affect functional aspects of the control of foot movement in a controlled setting, which is suitable for clinical evaluation. Muscle electrical activity also was shown to be a useful quantifier of the demyelination process. The multi-scale model encompasses neuronal ionic channels of spinal cord neurons up to a model of the foot and its muscles acting around the ankle joint when controlling force and foot position in a controlled lab experiment. The extension of such an approach to other peripheral nervous disorders or to spinal cord related pathologies (e.g., motoneuron diseases) seems quite feasible, provided that parameter data from patients are available to realize a biologically compatible model. Andre Fabio Kohn, Ph.D., Professor of Biomedical Engineering, University of Sao Paulo

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Postdoc positions in nanoscale modeling of neurons, synapses or astrocytes
by Erik De Schutter 20 Oct '22

20 Oct '22

The Computational Neuroscience unit at the Okinawa Institute of Science and Technology (https://www.oist.jp <https://www.oist.jp/>), Japan has been spearheading nanoscale stochastic modeling of astrocytes, neurons and synapses (https://groups.oist.jp/cnu <https://groups.oist.jp/cnu>). We have two postdoctoral positions open and Japan is issuing visa for such positions. The selected candidates will build on previous work in modeling of cerebellar or hippocampal neurons, synapses or astrocytes, neurons and synapses using our STEPS software (http://steps.sourceforge.net <http://steps.sourceforge.net/>), research project depending on experience and interests of the candidate. Previous experience in neural modeling required, preferentially as subject of PhD. Competences: A recent PhD in a relevant discipline such as neuroscience, molecular biology, biophysics or biochemistry. Experience in programming in Python. Fluent English conversation and writing skills. Benefits / Offer: A competitive salary and relocation package are offered with an initial 2 year contract. This an ideal position to gain experience in a prominent computational neuroscience lab and take part in our international collaborations. Please contact Prof. Erik De Schutter (erik(a)oist.jp <mailto:erik@oist.jp>) for inquiries.

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SNUFA22 spiking neural network workshop program (Nov 9-10)
by Goodman, Daniel F M 19 Oct '22

19 Oct '22

We are delighted to announce the finalised program for the SNUFA22 spiking neural network workshop. It's free to attend but you do need to register in advance: http://snufa.net/2022/ 9-10 November 2022, European afternoons. (Subscribe to the Google Calendar<https://calendar.google.com/calendar/u/0?cid=OTYzMGJmOWIyZmJjZjNmNjE0ZDMzN2…>.) Invited speakers. * Charlotte Frenkel<https://chfrenkel.github.io/> (TU Delft) * Priya Panda<https://intelligentcomputinglab.yale.edu/> (Yale) * Yiota Poirazi<http://dendrites.gr/> (Institute of Molecular Biology and Biotechnology IMBB) * Yonghong Tian<https://www.pkuml.org/> (Peking University) Contributed talks: Thomas Limbacher, Ozan Özdenizci, Robert Legenstein (TU Graz) Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity M. Nardin, J. W. Phillips, W. F. Podlaski, S. W. Keemink (IST Austria) Nonlinear computations in spiking neural networks through multiplicative synapses A. Subramoney, K. K. Nazeer, M. Schöne, C. Mayr, D. Kappel (University of Bochum) Beyond Biologically Plausible Spiking Networks for Neuromorphic Computing A. Galloni, A. Peddada, A. Milstein (Rutgers) Behavioral Timescale Synaptic Plasticity (BTSP) for biologically plausible credit assignment across multiple layers via top-down gating of dendritic plasticity W. F. Podlaski, C. K. Machens (Champalimaud) Universal function approximation in balanced spiking networks through convex-concave boundary composition B. Yin, F. Corradi, and S. M. Bohte (CWI) Training Dynamic Spiking Neural Network via Forward Propagation Through Time Z. Liao, D. Hadjiabadi, S. Terada, I. Soltesz, A. Losonczy (Columbia) A biologically plausible inhibitory plasticity rule for world-model learning in SNNs C. B. Currin, K. Stecher, C. Pfeffer, G. Novarino, and T. P. Vogels (IST Austria) Bridging the gap between artificial models and cortical circuits Plus around 30 posters. Many thanks! Dan Goodman, Friedemann Zenke, Katie Schuman, Tim Masquelier

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PhD openings in computational neuroscience, cognitive science, machine learning
by Rava A. da Silveira 18 Oct '22

18 Oct '22

*PhD openings in computational neuroscience, cognitive science, and interfaces with machine learning* The lab of Rava Azeredo da Silveira invites applications for *Doctoral Student* positions at IOB, University of Basel. Research questions will be chosen from a range of topics in theoretical/computational neuroscience and cognitive science, involving either data analysis or theory, and drawing on recent machine learning approaches. Candidates with backgrounds in mathematics, statistics, artificial intelligence, physics, computer science, engineering, biology, and psychology are welcome. Experience with data analysis and proficiency with numerical methods, in addition to familiarity with neuroscience topics and mathematical and statistical methods, are desirable. Equally desirable are a spirit of intellectual adventure, eagerness, and drive. The positions will come with highly competitive work conditions and salaries. For details, see https://www.silveira-lab.com/openings. *Application deadline:* For full consideration, please apply by 15 November 2020. *How to apply:* Please send the following information *in one single PDF, to * *silveira(a)iob.ch* <silveira(a)iob.ch>*:* 1. letter of motivation; 2. statement of research interests, limited to two pages; 3. curriculum vitæ. In all email correspondence, please include the mention “APPLICATION-PHD” in the subject header, otherwise the application will *not* be considered. Please also arrange for three letters of recommendations to be sent to the same email address.

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Postdoc openings in computational neuroscience, cognitive science, machine learning
by Rava A. da Silveira 18 Oct '22

18 Oct '22

*Postdoctoral openings in computational neuroscience, cognitive science, and interfaces with machine learning* The lab of Rava Azeredo da Silveira invites applications for *Postdoctoral Researcher* positions at IOB, University of Basel. Research questions will be chosen from a range of topics in theoretical/computational neuroscience and cognitive science, involving either data analysis or theory, and drawing on recent machine learning approaches. Candidates with backgrounds in mathematics, statistics, artificial intelligence, physics, computer science, engineering, biology, and psychology are welcome. Experience with data analysis and proficiency with numerical methods, in addition to familiarity with neuroscience topics and mathematical and statistical methods, are desirable. Equally desirable are a spirit of intellectual adventure, eagerness, and drive. The positions will come with highly competitive work conditions and salaries. For details, see https://www.silveira-lab.com/openings. *Application deadline:* For full consideration, please apply by 15 November 2020. *How to apply:* Please send the following information *in one single PDF, to * *silveira(a)iob.ch* <silveira(a)iob.ch>*:* 1. letter of motivation; 2. statement of research interests, limited to two pages; 3. curriculum vitæ including a list of publications; 4. any relevant publications that you wish to showcase. In all email correspondence, please include the mention “APPLICATION-POSTDOC” in the subject header, otherwise the application will *not* be considered. Please also arrange for three letters of recommendations to be sent to the same email address.

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Fully-funded computational neuroscience PhD at the University of Manchester
by Caroline Lea-Carnall 18 Oct '22

18 Oct '22

Link to project: https://www.findaphd.com/phds/project/bbsrc-dtp-neural-network-models-to-in… About the Project Neuroplasticity is the mechanism that underpins the brain’s ability to learn. It is an umbrella term that encompasses multiple processes occurring at different spatial and temporal scales (1, 2). The most commonly discussed type of plasticity is long-term potentiation (LTP) which is defined as an increase in efficacy between synapses of two neurons. Experiments designed to measure LTP are often done in cell slices or cultures using patch-clamp techniques. However, we often want to promote (and measure) plasticity in humans but its not clear how changes in synaptic efficacy manifest in macroscopic imaging measurements such as magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), or electroencephalography (EEG) that are available for use in humans. This project aims to link our detailed cellular-level knowledge of plasticity processes with systems-level observations in humans and is focussed on answering the following 2 questions: 1. How can we modulate plasticity non-invasively in the brain? 2. How can we measure plasticity in vivo? To answer these questions you will combine computational modelling of biophysically realistic large-scale neural networks that exhibit plasticity with cutting edge neuroimaging techniques to test the model predictions. The model will be adapted so that its output can be compared to the three major imaging techniques described above and you will determine how changes in connectivity between and within regions in the model predict changes in our imaging metrics. There will be a particular focus on developing an EEG marker of plasticity as this currently does not exist. Finally, you will test the model predictions in an imaging study combining stimulation, EEG, MRI and MRS in a proof-of-concept experiment in humans. This will provide us with a deeper understanding of how to modulate and measure plasticity that can be deployed in the future for medical applications of brain stimulation such as in Parkinson’s disease, depression and pain control. Eligibility Applicants must have obtained or be about to obtain a First or Upper Second class UK honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science, engineering or technology. Before you Apply Applicants must make direct contact with preferred supervisors before applying. It is your responsibility to make arrangements to meet with potential supervisors, prior to submitting a formal online application. How To Apply To be considered for this project you MUST submit a formal online application form - full details on eligibility how to apply can be found on the BBSRC DTP website https://www.bmh.manchester.ac.uk/study/research/bbsrc-dtp/<https://www.findaphd.com/common/clickCount.aspx?theid=147611&type=184&DID=1…> Your application form must be accompanied by a number of supporting documents by the advertised deadlines. Without all the required documents submitted at the time of application, your application will not be processed and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered. If you have any queries regarding making an application please contact our admissions team admissions.doctoralacademy(a)manchester.ac.uk<javascript:void(0)> Equality, Diversity and Inclusion Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-in…<https://www.findaphd.com/common/clickCount.aspx?theid=147611&type=184&DID=1…> ________________________________ Funding Notes Studentship funding is for 4 years. This scheme is open to both the UK and international applicants. We are only able to offer a limited number of studentships to applicants outside the UK. Therefore, full studentships will only be awarded to exceptional quality candidates, due to the competitive nature of this scheme.

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