- Comp-neuro - lists.cnsorg.org

Job Opportunity at INCF!
by INCF 03 Nov '22

03 Nov '22

Job Opportunity at INCF! Stockholm, SE: Want to join a friendly, international group passionate about neuroinformatics and the FAIR scientific environment? We’re hiring! The role includes: - managing INCF's scientific committees & councils, - developing communications materials, - maintaining training & education content, - maintaining updates on working group activities, - managing mentorship programs, and - assisting with INCF events. Candidates should be highly organized and service-minded with excellent written and spoken English. We are looking for a self-motivated and independent neuroscientist, computer scientist, or data scientist, preferably with experience in community engagement, open science practices, and scientific communications. The candidate should have strong time management skills and be able to multitask. Interpersonal skills are essential and we emphasize the person’s ability to contribute to a friendly work environment. Skills required: - MSc or PhD in computational neuroscience, neuroscience, data science, or computer science - Fluency in English - Strong organizational skills - Ability to prioritize tasks - Excellent and proven team-working ability - Tactful and diplomatic verbal and written interpersonal communication skills - Proficiency in MS Office - Proficiency in scientific writing (blog-style) - Experience with Adobe Creative Suite (mainly InDesign and Photoshop) Skills desirable: - Knowledge of Google apps, Zoom, Doodle, and other similar web applications for office use - Familiarity with social media platforms (Twitter, LinkedIn, Facebook, YouTube) - Graphical/layout skills Learn more and apply by November 30: bit.ly/INCFjobad /The INCF Team

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PhD Positions in Brain Imaging Computing at Lehigh University, US
by Yu Zhang 03 Nov '22

03 Nov '22

*PhD Positions in Brain Imaging Computing at Lehigh University, USA* The Brain Imaging and Computation Laboratory (BIC Lab) at Lehigh University has opening PhD positions in brain imaging computing. *Position description:* The research projects will focus on developing and applying a variety of machine learning/deep learning methods for brain imaging analysis and prediction. The successful applicants will contribute to research and development in artificial intelligence (AI)-driven neural biomarker discovery using advanced neuroimaging techniques (e.g., MRI and EEG) for precision medicine of brain diseases and brain-computer interaction. *Qualifications:* Successful applicants will have a Bachelor’s or Master’s degree in Electrical Engineering, Biomedical Engineering, Computer Science, or other related fields, and strong motivation to do high-quality research in novel brain imaging computing with machine learning. Additionally, strong quantitative skills and a programming background (Matlab and/or Python) are important. Previous research experiences in related fields and scientific publications in journals/conferences are preferred. *Lehigh University:* Lehigh University is a premier research university in the United States, consistently ranked in the top tier of national research universities each year. It is a coeducational, nondenominational, private university that offers a distinctive academic environment for undergraduate and graduate students from across the globe. The University campus is located in Pennsylvania’s scenic Lehigh Valley, with a driving distance of 1 hour to Philadelphia and of 2 hours to New York City. The application materials will be reviewed immediately once received. The expected starting time is in Spring or Fall 2023. Interested candidates should send their CV and a cover letter describing research accomplishments and interests to Dr. Yu Zhang at yuzi20(a)lehigh.edu Yu Zhang, PhD Assistant Professor Department of Bioengineering Department of Electrical and Computer Engineering Lehigh University Webpage: http://yuzhangresearch.weebly.com/ Email: yuzi20(a)lehigh.edu

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[Jobs] 2 Year Postdoc at the Institute for Neural Computation, Bochum, Germany
by Laurenz Wiskott 02 Nov '22

02 Nov '22

The Institute for Neural Computation of the Faculty for Informatics is looking for a postdoc (m,f,x) in the field of Computational Neuroscience for 2 years, 39,83 hours per week, E13 TVL The Institute for Neural Computation is part of the Faculty of Computer Science at the Ruhr-University Bochum, see https://www.ini.rub.de/. It focuses on the dynamics and learning of perception and behavior on a functional level but is otherwise very diverse, ranging from neurophysiology and psychophysics over computational neuroscience to machine learning and technical applications. There is an open position for a postdoc in the group „Theory of Neural Systems“ of Prof. Dr. Laurenz Wiskott to be filled as soon as possible. The position is planned for two years with salary level 100% TV-L E13, the standard German salary for postdocs. This position offers the opportunity to develop your own research profile and establish an independent research group. The research topic should be in the field of computational neuroscience on a system level, in particular modeling the visual system, episodic memory, or navigation in mammals. Collaborations with colleagues at the institute are welcome. extent: full-time duration: temporary beginning: as soon as possible application deadline: 21.11.2022 Your tasks: Independent research projects and publications. Acquiring third party funding. Teaching. A lot of room for own ideas and initiatives. Supervising student projects and your own PhD projects. Active participation in the local research environment. Your profile: Active participation in the local research environment. Solid knowledge in Computational Neuroscience. Potential to develop an original independent research agenda in one of the above-mentioned topics. Our offerings: An interesting interdisciplinary environment in the field of experimental and computational neuroscience / machine Learning. Opportunity to develop an independent research profile and your own research group. Opportunity to pursue further scientific qualification. A lot of room for own ideas and initiatives. Additional information: At the request of the applicant (m,f,x), the staff council may be involved in selection interviews. The load of teaching will be calculated according to § 3 of Lehrverpflichtungsverordnung (state of North Rhine-Westphalia). The Ruhr-Universität Bochum is one of Germany’s leading research universities, addressing the whole range of academic disciplines. A highly dynamic setting enables researchers and students to work across the traditional boundaries of academic subjects and faculties. To create knowledge networks within and beyond the university is RUB’s declared aim. The Ruhr-Universität Bochum stands for diversity and equal opportunities. For this reason, we favour a working environment composed of heterogeneous teams, and seek to promote the careers of individuals who are underrepresented in our respective professional areas. The Ruhr-Universität Bochum expressly requests job applications from women. In areas in which they are underrepresented they will be given preference in the case of equivalent qualifications with male candidates. Applications from individuals with disabilities are most welcome. Contact details for your application: Prof. Dr. Laurenz Wiskott, Phone: +49234 32 27997 Travel expenses for interviews cannot be refunded. For information on the collection of personal data in the application process see: https://www.ruhr-uni-bochum.de/en/information-collection-personal-data-appl…. ANR: 1267 until 21/11/2022 Applications (CV, transcript of records for PhD, MSc and BSc, statement of purpose) should be sent as a single pdf file to laurenz.wiskott(a)rub.de.

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Postdoctoral position for 2-photon imaging and holographic stimulation of neuronal avalanches in the cortex (Dietmar Plenz)
by Plenz, Dietmar (NIH/NIMH) [E] 02 Nov '22

02 Nov '22

A postdoctoral position for 2-photon imaging and holographic stimulation of neuronal avalanches in the cortex of behaving mice is available immediately in the Section of Critical Brain Dynamics of Dietmar Plenz at the National Institute of Mental Health, Bethesda, USA. The successful candidate will join our vibrant, collaborative, and interdisciplinary group to explore function and benefits of critical dynamics such as neuronal avalanches in cortical information processing. Our team utilizes numerous experimental techniques such as 2-photon imaging, controlled single cell stimulation with spatial-light modulation, and extracellular/intracellular recordings to study the emergent dynamics in large neuronal populations in vitro and in vivo. Our experimental approaches are complemented by elaborate computer simulations and theoretical studies in complex systems. We are located in the Porter Neuroscience Research Center on the main NIH campus in Bethesda, which provides ample opportunities to engage with a diverse neuroscience community for non-clinical and clinical research. To qualify for this position, you need a Ph.D. degree in neuroscience/physics or related discipline, some background in systems neuroscience, and an ability to work in a multidisciplinary team. Special considerations are given to applicants with training in imaging, in vivo physiology, laser optics, computational approaches. Advanced programming skills, in MATLAB, and/or Python, are of advantage but not required. The position comes with a commitment of at least 2 years and can be extended for up to 5 years. Interested and qualified individuals should send a copy of their curriculum vitae and names of three references to Dietmar Plenz at plenzd(a)mail.nih.gov<mailto:plenzd@mail.nih.gov>. The NIH is dedicated to building a community in its training and employment programs and encourages the application and nomination of qualified women, minorities, and individuals with disabilities. Postdoc Positions at the NIH View - Office of Intramural Training & Education at the National Institutes of Health<https://www.training.nih.gov/postdoc_jobs_nih/view/_31/10120/PIHSNABM_11120…>

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Two postdoc positions in Computational Neuroscience in Shanghai
by yy227 02 Nov '22

02 Nov '22

Dear colleagues, Two open postdoc positions are available in the Computational Neuroscience Lab led by Professor Yuguo Yu at Fudan University, Shanghai, China. We are looking for motivated scientists or engineers with Ph.D in multidisciplinary fields like Physics, Neuroscience, Mathematics, or Computer Sciences, with experience and passion in the study of neural information processing mechanisms and algorithms for brain-inspired intelligence. The major scientific questions studied recently in our groups are: 1. What computational rules or physical principles does the brain circuit follow in the long-term evolution? (Yu Y et al., JCBFM 2018; Wang X et al., PNAS 2020; Yu Y et al., Cerebral Cortex 2022) 2. How to develop Spiking neural networks (SNNs) that mimic information encoding and decoding in the brain and can energy efficiently process Spatio-temporal information through discrete and sparse spikes. (Yu Y et al., J. Neurosci.2014; Du M et al., PLoS Comp.Biol.2018; Zhang J et al., Research 2022) . 3. To develop computational behavior models or deep neural networks for higher cognitive functions, such as inhibitory control, cognitive flexibility, and working memory, so as to understand the mechanism of cognition and its impairment in psychiatric disorders. For this direction, contact: Prof. Luo, qluo(a)fudan.edu.cn. (Recent publications: JAMA Psychiatry 2019; 76(4):435-445; NeuroImage 2022, 263,119585.) The duration of the postdoc is two years with the possibility of renewal. Postdoctoral fellows will receive a generous salary and an allocation for research and travel expenses. Please email for more details. Basic Qualifications: Candidates should have backgrounds in one or more of the following areas: physics, machine learning, statistics, computational neuroscience, computer science, applied mathematics, or electrical engineering. The candidate will be expected to publish scholarly papers, attend internal, domestic, and international conferences and meetings, as well as take on a mentorship role for undergraduate and graduate students. Contact: Required application documents include a cover letter, CV, a statement of research interests, and up to three representative papers. Candidates are also required to submit the names and contact information for at least three references, and the application is complete only when three letters have been submitted. We encourage candidates to apply by Feb 31, 2022, but will continue to review applications until the positions are filled. Contact Information: Yuguo Yu (yuyuguo(a)fudan.edu.cn) Qiang Luo (qluo(a)fudan.edu.cn) Equal Opportunity Employer Fudan University is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service, pregnancy and pregnancy-related conditions, or other protected status.

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Postdoctoral and doctoral studies in the neuroscience of real-time, embodied decision-making and action planning
by Paul Cisek 01 Nov '22

01 Nov '22

Postdoctoral and doctoral studies in the neuroscience of real-time, embodied decision-making and action planning Department of Neuroscience, University of Montreal Applications are invited for postdoctoral and doctoral studies in systems neuroscience, in the laboratories of Paul Cisek and Andrea Green at the University of Montreal. Our research investigates the neural mechanisms of decision-making and action planning in humans and non-human primates using computational models of the nervous system as well as behavioral experiments, transcranial magnetic stimulation, and multi-electrode recording in multiple regions of the cerebral cortex and basal ganglia. New projects will use virtual reality to study naturalistic behavior in both humans and non-human primates and develop computational models of real-time action selection and control. Additional collaborative projects include studies of decision-making during ongoing action and movement through space, MEG studies of dynamic decision-making in humans (with Karim Jerbi), and computational modeling of neural circuits and artificial learning systems (with Guillaume Lajoie and Irina Rish). For more information, see: https://cisek.org/pavel/ and https://neurosciences.umontreal.ca/recherche/les-chercheurs/andrea-green/. Multiple positions are available. All students with a strong background in biological sciences, engineering, mathematics, computer science, physics or psychology and an interest in system-level study of the brain are encouraged to apply. Prior experience in neurophysiology, behavioral neuroscience and/or computational modeling of neural systems is highly desirable. Depending on the applicant's qualifications and interests, they will help to design and conduct behavioral and neurophysiological experiments, analyze data, develop theoretical models of neural systems, prepare manuscripts for publication and participate in international conferences. Interested candidates are asked to send a curriculum vita, copies of academic transcripts, a statement of research interests and the names and contact information for two references, to Paul Cisek (paul.cisek(a)umontreal.ca<mailto:paul.cisek@umontreal.ca>) and Andrea Green (andrea.green(a)umontreal.ca<mailto:andrea.green@umontreal.ca>). Applications will be accepted until the positions are filled, but preference will be given to applications received before November 30, 2022. Interviews will be possible at the Society for Neuroscience meeting (San Diego, CA, November 12-16, 2022). Paul Cisek, PhD Département de neurosciences Université de Montréal Physical: 2960 chemin de la tour, local 4117 Montréal, QC H3T 1J4 CANADA Mailing: CP 6128 Succursale centre-ville, Montréal, QC H3C 3J7 CANADA e-mail: paul.cisek(a)gmail.com<mailto:paul.cisek@gmail.com> Web: www.cisek.org/pavel<http://www.cisek.org/pavel>

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Dec 1 deadline: PhD student opening in the Developmental Cognitive Neuroscience lab (Bayet lab) at American University, Washington DC
by Laurie Bayet 01 Nov '22

01 Nov '22

Dr. Bayet (bayet(a)american.edu) assistant professor of Neuroscience at American University, is anticipating *accepting a PhD student for Fall 2023* through the Behavioral, Cognition, and Neuroscience (BCaN) program. The *application deadline is Dec 1st*, and prospective students may apply now at: https://www.american.edu/cas/neuroscience/phd/requirements.cfm (GRE optional). Applicants should mention the name(s) of the faculty they are interested in working with within their statement of purpose. The program provides 4 years of funding. Dr. Bayet directs the *Developmental Cognitive Neuroscience lab at American University*, which focuses on *infant cognitive development and high-level vision* research. Current projects in the lab combine electro-encephalography (EEG), eye-tracking, behavioral methods, and/or computational (e.g., machine learning) tools to uncover how infants and young children represent and understand complex visual objects, with particular focus on those visual objects that are relevant to affective, social communication (e.g., facial movements). Dr. Bayet's work has been recognized with a Rising Star award from the Association for Psychological Science (APS), and a Distinguished Early Career Contribution Award from the International Congress of Infant Studies. Learn more at: https://www.american.edu/cas/faculty/bayet.cfm and https://www.bayetlab.com/ The PhD student will have the opportunity to *contribute to ongoing* *NSF-funded research* in collaboration with Drs. Alexis Black (UBC), Lauren Emberson (UBC), and Richard N. Aslin (Haskins/Yale). The project, entitled “*Grounding computational models of vision with infant brain data*”, uses EEG and multivariate “decoding” to characterize infants' neural representations of visual objects, compare them to those of artificial neural networks, and assess relationships between language and visual representations (NSF award # 2122961 <https://www.nsf.gov/awardsearch/showAward?AWD_ID=2122961>). The Developmental Cognitive Neuroscience Laboratory is part of the Neuroscience Department (https://www.american.edu/cas/neuroscience/ ) and the Center for Neuroscience and Behavior ( https://www.american.edu/cas/center-neuroscience/ ) at American University. American University provides a stimulating intellectual environment, just 2 miles from downtown Washington DC. DC offers a vibrant research community, and American University enjoys proximity to other notable research institutions such as the National Institutes of Health. With extensive public transit, an exciting cultural and restaurant scene, many museums and public parks, and proximity to other green spaces in the surrounding region (e.g., Appalachian trail, Shenandoah National Park), Washington DC consistently ranks amongst the top US metropolitan areas for quality of life. Prior experience with developmental/neuroimaging research or programming/machine learning (we use Python, Matlab, and/or R) are preferred but not required, as training will be provided. Interested applicants may contact Dr. Bayet at bayet(a)american.edu for any inquiry. Selected recent lab publications: Ashton, K., Zinszer, B. D., Cichy, R. M., Nelson III, C. A., Aslin, R. N., & Bayet, L. (2022). Time-resolved multivariate pattern analysis of infant EEG data: A practical tutorial. *Developmental cognitive neuroscience*, *54*, 101094. https://doi.org/10.1016/j.dcn.2022.101094 Bayet, L. (2022). How infants learn from a world of faces: Implications for racial biases and mask-wearing. *Policy Insights from the Behavioral and Brain Sciences*, 9(1), 65-72. https://doi.org/10.1177/23727322211068007 Bayet, L., Perdue, K. L., Behrendt, H. F., Richards, J. E., Westerlund, A., Cataldo, J. K., & Nelson III, C. A. (2021). Neural responses to happy, fearful and angry faces of varying identities in 5-and 7-month-old infants. *Developmental cognitive neuroscience*, 47, 100882. https://doi.org/10.1016/j.dcn.2020.100882 Bayet, L., Zinszer, B. D., Reilly, E., Cataldo, J. K., Pruitt, Z., Cichy, R. M., ... & Aslin, R. N. (2020). Temporal dynamics of visual representations in the infant brain. *Developmental cognitive neuroscience* , *45*, 100860. https://doi.org/10.1016/j.dcn.2020.100860 -- Laurie Bayet, PhD (hear name <https://namedrop.io/lauriebayet>) Assistant Professor of Neuroscience, American University (202) 885-1719

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Postdoc position in modelling the effects of neuromodulation on balanced networks
by Fleur Zeldenrust 01 Nov '22

01 Nov '22

We are looking for a postdoctoral researcher to work on the Vidi project 'Top-down neuromodulation and bottom-up network computation, a computational study' and *study the effects of neuromodulators in balanced networks*. You will use cellular and behavioural data on the effects of dopamine, acetylcholine and serotonin in mouse barrel cortex gathered by our department over the past five years, to bridge the gap between single cell, network and behavioural effects. You will use the balanced network framework to study network activity under neuromodulation. In order to do this, you will develop a balanced network description of the barrel cortex, with realistic barrel cortex properties (see https://doi.org/10.1007/s12021-022-09576-5) Next, you will incorporate the cellular effects of dopamine, acetylcholine and serotonin that we have measured over the previous years (see https://doi.org/10.1093/gigascience/giy147 and https://doi.org/10.1101/2022.01.12.476007) into the network, and investigate their effects on overall network activity and behaviour. More particularly, through simulations and analytical derivations, you will research the effects of neuromodulators on the stability of the balanced state, synchrony, regularity and chaos. You will build on the single cell data, models and analysis methods available in our group, and your results will be incorporated into our group's further research to develop and validate machine learning and efficient coding models of (somatosensory) perception. We are therefore looking for a team player who can work well with our other group members and is willing to both learn from them and share their knowledge. *Profile* - You hold a PhD in computational neuroscience, mathematics, physics, computer science, AI or a related discipline. - Preferably, you have experience in working with balanced networks and can perform both network simulations and analytical derivations such as mean field approximations and chaos descriptions. - You are a highly motivated, independent, critical, and creative researcher who wants to bridge the gap between real data and abstract theoretical models. - You are a team player, ready to collaborate in a multidisciplinary research group. - You have an excellent command of spoken and written English. - You have experience in coding (Python and/or Matlab). *We are* You will be appointed at the Biophysics of Neural Computation group <https://www.ru.nl/donders/research/theme-4-neural-computation-neurotechnolo…> , Donders Center for Neuroscience <https://www.ru.nl/science/dcn/>, Donders Institute for Brain, Cognition and Behaviour <https://www.ru.nl/donders/>., at the Radboud University. <http://www.ru.nl/> This vibrant and multidisciplinary institute studies the organisation and function of neural circuits across scales and techniques, from genes and proteins to behaviour and from in vitro and in vivo experiments to computational modelling. It provides an open and international environment, where young scientists from different backgrounds share a fascination for the interaction between brain structure and function. For postdoctoral researchers, there is a lively community <https://www.ru.nl/donders/talent-education/postdoctoral-researchers/> and specialised support. *We offer* It concerns an employment for 0.8 - 1.0 FTE. - The gross monthly salary amounts to a minimum of €2,960 and a maximum of €4,670 based on a 38-hour working week, depending on previous education and number of years of relevant work experience (salary scale 10). - You will receive 8% holiday allowance and 8.3% end-of-year bonus. - It concerns a temporary employment for 26 months. - You will be able to use our Dual Career and Family Care Services. Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment and help your family settle in Nijmegen. - Working for us means getting extra days off. In case of full-time employment, you can choose between 30 or 41 days of annual leave instead of the legally allotted 20. *Practical information and applying* You can apply until 1 December 2022, exclusively on the website below. Kindly address your application to Fleur Zeldenrust. Please fill in the application form and attach the following documents: - A letter of motivation (max. 2 pages). - Your CV including a publication list. - A copy of a first-authored publication. - Contact details of two academic referees. The first round of interviews will take place on Thursday 8 December. You would preferably begin employment on 1 January 2023. See also: https://www.ru.nl/en/working-at/job-opportunities/postdoctoral-researcher-i… -- Fleur Zeldenrust Assistant Professor Donders Institute for Brain, Cognition and Behaviour Donders Centre for Neuroscience Faculty of Science, Radboud University Heyendaalseweg 135, room HG 00.111 6525 AJ Nijmegen, the Netherlands tel +31 24 36 53195 fleurzeldenrust.nl *Due to my own family/work balance, you may receive emails from me outside of normal working hours. I do not expect a response from you outside of your own working pattern, nor do I expect an immediate response when you are working.*

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Fully funded Phd position in the intersection of neuroscience and AI
by Guozhang Chen 30 Oct '22

30 Oct '22

We (the group of Prof. Wolfgang Maass) accept applications for a fully funded Phd position for research in the intersection of neuroscience and AI. This Phd student will work with our team on reverse engineering data-based models for cortical microcircuits and their learning capabilities, as for example in --Analysis of visual processing capabilities and neural coding strategies of a detailed model for laminar cortical microcircuits in mouse V1 (G. Chen, F. Scherr, W. Maass).Science Advances (Nov. 2, 2022), https://www.biorxiv.org/content/10.1101/2021.12.07.471653v3?versioned=t <https://www.biorxiv.org/content/10.1101/2021.12.07.471653v3?versioned=t> --A solution to the learning dilemma for recurrent networks of spiking neurons (Bellec, G., Scherr, F., Subramoney, A., Hajek, E., Salaj, D., Legenstein, R., & Maass, W.) Nature Communications 2020, 11(1), 1-15. In addition, the Phd student will work on the development of brain-inspired architectures and algorithms for AI, like in --Local prediction-learning enables neural networks to plan (C. Stoeckl, W.Maass) https://www.biorxiv.org/content/10.1101/2022.10.17.512572v1 <https://www.biorxiv.org/content/10.1101/2022.10.17.512572v1>, and for highly energy-efficient neuromorphic hardware, as in --A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware (A Rao, P Plank, A Wild, W Maass), Nature Machine Intelligence 4 (5), 467-479. https://igi-web.tugraz.at/PDF/261.pdf <https://igi-web.tugraz.at/PDF/261.pdf> In order to qualify for this Phd-position you need to have a master degree in computer science or related areas, very good skills in mathematics/theory, and programming experience for GPUs. You should also have an excellent record,demonstrations of your research potential, and be strongly motivated to collaborate with us on understanding “how the brain works”. If you qualify, please send me your CV, transcripts, names of referees, as well as links to your master thesis, papers, and other pertinent documents to email:<maass(a)igi.tugraz.at> Guozhang Chen on behalf of Prof. Dr. Wolfgang Maass Institut fuer Grundlagen der Informationsverarbeitung Technische Universitaet Graz Inffeldgasse 16b , A-8010 Graz, Austria http://www.igi.tugraz.at/maass/Welcome.html <http://www.igi.tugraz.at/maass/Welcome.html>

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Faculty position in computational neuroscience/machine learning at Stony Brook University
by Giancarlo La Camera 29 Oct '22

29 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 Stony Brook University

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PhD program in Systems/Computational/Cognitive neuroscience at U of Oregon
by Luca Mazzucato 28 Oct '22

28 Oct '22

We are accepting applications to the Interdepartmental Neuroscience Graduate Program (INGP) <https://ion.uoregon.edu/training-programs/graduate-fellows> at the Institute of Neuroscience, a robust graduate training in Neuroscience across departments at the University of Oregon. The goal of INGP is to train students to think independently, creatively, and critically about problems in neuroscience. We aim to train students in a variety of skills that will prepare students for successful research, teaching, policy, or industry career. Students can enter INGP through the departments of biology, human physiology, psychology, mathematics, physics, computer and information science, and the Knight Campus, depending on their interests. The majority of our students enter through the department of biology, which allows students to complete three rotations during their first year, in order to help students identify a laboratory in which to do their dissertation research. Students who enter through psychology, physiology, and mathematics begin in their dissertation labs immediately. Regardless of how students enter INGP, they are provided with a set of mentors at the peer and faculty levels. All graduate students are required to teach for at least one academic year during their graduate career; at least a portion of this teaching takes place the first year. *Training Program* Students typically fall into a defined training program, however, training can be tailored to fit a student’s need and research interest. We offer two training tracks: Systems, Cognitive and Theoretical - Courses: cellular neuroscience, systems neuroscience, cognitive neuroscience, computational neuroscience, combinatorics, stochastic processes, neural networks. - Journal clubs: systems neuroscience, theoretical neuroscience. - Meetings: neural circuits and behavior, zebrafish groupie, joint theory lab meetings.

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Doctoral studies in Computational/Theoretical Neuroscience at NYU
by Eero Simoncelli 28 Oct '22

28 Oct '22

New York University is home to a thriving interdisciplinary community of researchers using computational and theoretical approaches in neuroscience. We are interested in exceptional PhD candidates with strong quantitative training (e.g., physics, mathematics, engineering) coupled with a clear interest in scientific study of the brain. A listing of faculty, sorted by their primary departmental affiliation, is given below. Doctoral programs are flexible, allowing students to pursue research across departmental boundaries. Nevertheless, admissions are handled separately by each department, and students interested in pursuing graduate studies should submit an application to the program that best fits their goals and interests. Center for Neural Science (CNS), Graduate School of Arts & Sciences (deadline: 1 December) [https://neuroscience.nyu.edu/program.html, and https://as.nyu.edu/cns/DoctoralProgram.html] * SueYeon Chung - NeuroAI and geometry. * Andre A. Fenton - Molecular, neural, behavioral, and computational aspects of memory. * Paul W. Glimcher - Decision-making in humans and animals. Neuroeconomics. * David Heeger (also in Psychology) - Computational neuroscience, vision, attention. * Roozbeh Kiani - Vision and decision-making. * Wei Ji Ma (also in Psychology) - Perception, working memory, and decision-making. * Tony Movshon - Vision and visual development. * Bijan Pesaran - Neuronal dynamics and decision-making. * Alex Reyes - Functional interactions of neurons in a network. * John Rinzel (also in Mathematics) - Biophysical mechanisms and theory of neural computation. * Cristina Savin (also in the Center for Data Science) - Computational models of learning and memory, machine learning. * Robert Shapley - Visual physiology and perception. * Eero Simoncelli - Computational vision and audition. * Xiao-Jing Wang - Computational neuroscience, decision-making and working memory, neural circuits. * Alex Williams - Statistical analysis of neural data. Neuroscience Institute, School of Medicine (deadline: 1 December) [https://neuroscience.nyu.edu/program.html, and https://med.nyu.edu/departments-institutes/neuroscience/] * Gyorgy Buzsaki - Rhythms in neural networks. * Dmitri Chklovskii (also in the Simons Foundation) - Neural computation and connectomics. * Biyu He - Large-scale brain dynamics underlying human cognition. * Dmitry Rinberg - Sensory information processing in the behaving animal. * Shy Shoham - Methods for controlling, imaging, and analyzing neural systems. * Mario Svirsky - Auditory neural prostheses; experimental/computational studies of speech production/perception. Psychology, Cognition & Perception program (deadline: 1 December) [http://as.nyu.edu/psychology/graduate/phd-cognition-perception.html] * Todd Gureckis - Memory, learning, and decision processes. * Brenden Lake (also in the Center for Data Science) - Computational modeling of cognition, deep learning. * Michael Landy - Computational approaches to vision. * Laurence Maloney - Mathematical approaches to psychology and neuroscience. * Denis Pelli - Visual object recognition. * Jonathan Winawer - Visual perception and memory. Mathematics (deadline: 18 December) [https://gsas.nyu.edu/admissions/arc/programs/mathematics.html] * David McLaughlin - Nonlinear wave equations, computational visual neuroscience. * Aaditya Rangan - Computational neurobiology, numerical analysis. * Charles Peskin - Mathematical biology. * Daniel Tranchina - Information processing in the retina. * Lai-Sang Young - Dynamical systems, statistical physics, computational modeling and theoretical neuroscience. Data Science (deadline: 12 December) [https://cds.nyu.edu/phd-program/] * Joan Bruna (also in Computer Science) - Machine learning, signal/image processing. * Kyungyun Cho (also in Computer Science) - Machine learning, natural language processing. * Carlos Fernandez-Granda (also in Mathematics) - Optimization methods for medical imaging, neuroscience, computer vision. * Grace Lindsay (also in Psychology) - Machine learning models of the brain/mind. * Mengye Ren (also in Computer Science) - Machine learning, computer vision, representation learning. Physics (deadline: 30 December) [https://as.nyu.edu/physics/programs/graduate.html] * Marc Gershow - Perception, decision-making, and learning in neural circuits. Computer Science (deadline: 12 December) [http://www.cs.nyu.edu/home/phd/] * Davi Geiger - Computational vision and learning. * Yann LeCun - Machine learning, computer vision, robotics, computational neuroscience. Economics (deadline: 18 December) [https://as.nyu.edu/econ/graduate/phd.html] * Andrew Caplin - Economic theory, neurobiology of decision. * Andrew Schotter - Experimental economics, game theory, neurobiology of decision.

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EPFL - Faculty position at the intersection of computational and life sciences
by Mathis Alexander 26 Oct '22

26 Oct '22

Dear colleagues, The Schools of Computer and Communication Sciences (IC) and Life Sciences (SV) at EPFL invite applications for a faculty position at the intersection of computational and life sciences. We seek candidates who use machine learning and/or other original computational approaches to solve challenges in life sciences. The appointment could be either at the assistant professor or tenured level. Candidates must have an outstanding academic record, a compelling vision, demonstrated impact, and a strong commitment to excellence in teaching and mentoring students. EPFL attracts top students from all over the world and offers competitive salaries, generous research funding and excellent research infrastructure. Switzerland has an exceptionally high human development index and consistently ranks highly in quality of life, economic competitiveness, and innovation. Applicants must submit a cover letter, a curriculum vitae including a publication list, brief statements of research and teaching interests, and contact information of at least 3 references (5 for tenured positions) who are ready to supply a letter upon request. To apply, go to: https://facultyrecruiting.epfl.ch/position/40599570 Screening will start on December 1, 2022, but applications submitted after this date will also be considered. Questions can be addressed to: Profs. George Candea and Matteo Dal Peraro Co-chairs of the Faculty Recruiting Committee E-mail: recruiting.icsv(a)epfl.ch<mailto:recruiting.icsv@epfl.ch> For more information on our schools, please visit https://sv.epfl.c<https://sv.epfl.ch/>h<https://sv.epfl.ch/> and https://ic.epfl.ch<https://ic.epfl.ch/> EPFL is an equal opportunity employer and family-friendly university. It is committed to increasing the diversity of its faculty. It strongly encourages women to apply.

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EPFL AI4Science Postdoctoral Fellowship: Deadline Oct 31st.
by Mathis Alexander 26 Oct '22

26 Oct '22

Dear colleagues, The EPFL AI4Science Fellowship gives outstanding and highly motivated young researchers the chance to collaborate with a broad range of EPFL faculty on accelerating the use and furthering the understanding of machine learning methods in the scientific discovery process. The Fellowship focuses on excellence and interdisciplinarity. Therefore fellows will work with several laboratories at EPFL and will be granted ample freedom to develop their own research agenda. We expect fellows to contribute to a vibrant and multidisciplinary community of researchers passionate about the transformation of science with new data-driven methods. Initial appointments will be made for one year, with the expectation of renewal for at least a second year, upon agreement of the AI4Science scientific committee. The salary follows the generous scale for EPFL post-doctoral researchers. Starting date is flexible. Application deadline: October 31st 2022 More details are available at https://www.epfl.ch/research/domains/cis/epfl-ai4science/call-for-fellows/ Best wishes, Alexander Mathis [cid:clip_image001.png] Alexander Mathis Tenure Track Assistant Professor people/alexander.mathis mathislab.org<http://mathislab.org>

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Neuroscience Gateway (NSG) Virtual workshop as a part of Society for Neuroscience Annual meeting, San Diego Nov 2022
by Majumdar, Amitava 26 Oct '22

26 Oct '22

Hello, We are happy to announce that the Neuroscience Gateway (NSG) will host a Virtual workshop as a part of the Society for Neuroscience Annual Meeting in San Diego, November 2022. Date and time of the virtual NSG workshop: November 12, 8:30 AM - 12:30 PM USA Pacific Time Zone. We have distinguished speakers who are early career researchers to senior researchers. They will present their work, many of which utilize NSG or are neuroscience software projects and are available on NSG for neuroscientists to use on high performance computing resources. Registration is free but required by November 9th. Please register if you plan to attend. Title of the virtual workshop: Neuroscience Gateway - Enabling Large Scale Modeling, Data Processing and Dissemination of Software Details about the list of speakers, abstract of talks and registration are available here: http://www.nsgportal.org/NSG_HPAC_SfN2022_Wkshop.web.htm Thank you. Regards. NSG Team

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Faculty positions at Washington University in St Louis
by Geoffrey Goodhill 26 Oct '22

26 Oct '22

Electrical & Systems Engineering: Tenure-Track Faculty Positions Washington University in St Louis https://apply.interfolio.com/114838 The Electrical and Systems Engineering department at Washington University in St. Louis invites applications for multiple tenure-track faculty positions with an effective start date on or after July 1, 2023. Candidates should have earned a Ph.D. or equivalent degree in electrical engineering, systems engineering, computer engineering or a closely related discipline. Washington University is a highly-selective national research university with a strong tradition of research excellence. The University’s strategic plan, released in 2022, seeks growth of top-tier research, scholarship, and creative practice with an emphasis on transdisciplinary and cross-school research. Included in this plan are foci related to applications in medicine, public health, infrastructure, and addressing pressing societal challenges. Accordingly, we seek both junior and senior applicants who will contribute to research efforts across ESE, including in several emphasis areas: information and decision systems, including autonomous systems and human-machine interaction network science, including social systems and large-scale data analysis imaging science, including signal processing and computational imaging engineering brain science, including theory, models and methods for brain-inspired computation and for measuring and manipulating neural circuits quantum sensing and imaging, including science and technology for detection and estimation beyond classical physics. Candidates interested in this area are encouraged to note University-wide growth in quantum technology at https://quantumleaps.wustl.edu/. Candidates may apply to the quantum cluster search in addition to the ESE search. Equity, diversity and inclusion are core values at Washington University, and candidates will need to demonstrate the ability to create inclusive classrooms and environments in which a diverse array of students can learn and thrive. Candidates who will contribute to the diversity of the department are strongly encouraged to apply. Successful applicants will have a primary appointment in the department of Electrical and Systems Engineering (ese.wustl.edu) with the possibility of joint appointments in other departments. The faculty member will be expected to teach undergraduate and graduate courses in electrical and systems engineering, participate in university service, and establish a thriving externally-funded research program. Faculty positions are open for all levels. Applications should include: (1) a cover letter that identifies the candidate’s three most significant publications and describes their interest in the position; (2) a curriculum vitae; (3) a research plan for the next five years that should not exceed three pages, and should highlight the problem(s) or set of questions to be investigated, the envisioned approach, a mentoring strategy, and the proposed funding sources; (4) a statement of teaching interests and philosophy; (5) a statement describing contributions to and future plans for enhancing equity, diversity and inclusion; and (6) a list of at least three references to (https://apply.interfolio.com/114838) Priority will be given to completed applications (including submitted reference letters) received before December 15, 2022. However, applications will be accepted at any time and will be considered until the positions are filled. Professor Geoffrey J Goodhill Departments of Neuroscience, Developmental Biology, Biomedical Engineering, Computer Science and Engineering, and Electrical and Systems Engineering Washington University in St Louis St. Louis, MO 63110 g.goodhill(a)wustl.edu https://neuroscience.wustl.edu/people/geoffrey-goodhill-phd

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Postdoc positions at Harvard
by Cengiz Pehlevan 25 Oct '22

25 Oct '22

Dear colleagues, I want to point to a few postdoctoral fellow positions at Harvard for candidates in computational/theoretical neuroscience: 1. The George F. Carrier Postdoctoral Fellowship: https://academicpositions.harvard.edu/postings/11642 <https://academicpositions.harvard.edu/postings/11642> 2. Postdoctoral Fellow in Theoretical Neuroscience and/or Theory of Neural Computation: https://academicpositions.harvard.edu/postings/11671 <https://academicpositions.harvard.edu/postings/11671> 3. The Harvard Data Science Postdoctoral Fellows: https://datascience.harvard.edu/data-science-postdoctoral-fellows <https://datascience.harvard.edu/data-science-postdoctoral-fellows> 4. Postdoctoral fellow in the Foundations of Machine Learning: https://academicpositions.harvard.edu/postings/11762 <https://academicpositions.harvard.edu/postings/11762> Please feel free to write to me with questions. Best wishes, Cengiz

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INCF/OCNS SoftwareWG Dev session: Denis Alevi: Brian2CUDA: November 3, 2022, 1600 UTC over Zoom
by Ankur Sinha 25 Oct '22

25 Oct '22

Dear all, Please join us for our next dev session on Brian2CUDA: https://ocns.github.io/SoftwareWG/2022/10/18/dev-session-denis-alevi-brian2… Denis Alevi will introduce the Brian2CUDA tool in this session, and discuss its development. We will also have a discussion on GPU based simulation in neuroscience after the presentation. - Date: Thursday, November 3, 2022, 1600 UTC (Click here to see your local time: https://www.timeanddate.com/worldclock/fixedtime.html?msg=Dev+session%3A+De…) - Location (Zoom, login required): https://ucl.zoom.us/j/95692778384?pwd=VldIQ3hPTU1zczNpYjQxSSt4Z25xdz09 The abstract for the talk is below: Graphics processing units (GPUs) are widely available and have been used with great success to accelerate scientific computing in the last decade. These advances, however, are often not available to researchers interested in simulating spiking neural networks, but lacking the technical knowledge to write the necessary low-level code. Writing low-level code is not necessary when using the popular Brian simulator, which provides a framework to generate efficient CPU code from high-level model definitions in Python. Here, we present Brian2CUDA, an open-source software that extends the Brian simulator with a GPU backend. Our implementation generates efficient code for the numerical integration of neuronal states and for the propagation of synaptic events on GPUs, making use of their massively parallel arithmetic capabilities. We benchmark the performance improvements of our software for several model types and find that it can accelerate simulations by up to three orders of magnitude compared to Brian’s CPU backend. Currently, Brian2CUDA is the only package that supports Brian’s full feature set on GPUs, including arbitrary neuron and synapse models, plasticity rules, and heterogeneous delays. When comparing its performance with Brian2GeNN, another GPU-based backend for the Brian simulator with fewer features, we find that Brian2CUDA gives comparable speedups, while being typically slower for small and faster for large networks. By combining the flexibility of the Brian simulator with the simulation speed of GPUs, Brian2CUDA enables researchers to efficiently simulate spiking neural networks with minimal effort and thereby makes the advancements of GPU computing available to a larger audience of neuroscientists. References: - Publication: Brian2CUDA: flexible and efficient simulation of spiking neural network models on GPUs: https://www.frontiersin.org/articles/10.3389/fninf.2022.883700/abstract - Documentation: https://brian2cuda.readthedocs.io/en/latest/ - Source code: https://github.com/brian-team/brian2cuda We hope to see you there. On behalf of the INCF/OCNS Software working group, -- Thanks, Regards, Ankur Sinha (He / Him / His) | https://ankursinha.in Research Fellow at the Silver Lab, University College London | http://silverlab.org/ Free/Open source community volunteer at the NeuroFedora project | https://neuro.fedoraproject.org Time zone: Europe/London

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Upcoming Faculty Opening in Theoretical Neuroscience
by Lin, I-Chun 25 Oct '22

25 Oct '22

The Gatsby Computational Neuroscience Unit intends to recruit one Principal Investigator in Theoretical Neuroscience at any academic rank (UCL grades 8 to 10; Lecturer/Group Leader-level to Professorial). We seek candidates who focus on the mathematical underpinnings of adaptive intelligent behaviour in animals or develop mathematical tools and models to understand how neural circuits and systems function. We are particularly interested in researchers who are well placed to take advantage of collaborations within the unit; with our sister institute, the Sainsbury Wellcome Centre for Neural Circuits and Behaviour; and elsewhere at UCL. Gatsby faculty members pursue and develop their own lines of research within the broad remit of the unit’s focus on the mathematical principles of learning, perception and action in brains and machines. For an overview of our current work, please see www.ucl.ac.uk/gatsby/research-0<http://www.ucl.ac.uk/gatsby/research-0>. We maintain a singular and cohesive research culture, emphasising interaction and collaboration both within the unit and beyond. Our faculty members teach and supervise at graduate level, primarily as part of the unit’s international PhD programme. We encourage informal enquiries about this upcoming position. Interest from women and those from an ethnic minority background is particularly welcome, as they are under-represented within UCL at these levels. Please direct enquiries to I-Chun Lin (Scientific Programme Manager, i.lin at ucl.ac.uk). We will be best placed to respond to enquiries that include a short CV and a brief sketch of research interests. www.ucl.ac.uk/gatsby/vacancies<http://www.ucl.ac.uk/gatsby/vacancies> -- I-Chun Lin, PhD Scientific Programme Manager Gatsby Computational Neuroscience Unit, UCL www.ucl.ac.uk/gatsby<http://www.ucl.ac.uk/gatsby> | @GatsbyUCL<https://twitter.com/GatsbyUCL>

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Three 3-year positions in teaching (general AI) in Groningen, NL
by Herbert Jaeger 24 Oct '22

24 Oct '22

The AI Department in the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence (https://www.rug.nl/research/bernoulli/) at the University of Groningen (https://www.rug.nl/) offers three 3-year positions for teaching in general AI, with competitive salaries, in a most welcoming and high-ranked working environment (top-100 university, https://www.rug.nl/about-ug/profile/facts-and-figures/position-internationa…) The application deadline is November 7, 2022. Formal prerequisites are a PhD degree; outstanding holders of a MSc degree will also be considered. Details can be found at https://www.rug.nl/about-ug/work-with-us/job-opportunities/?details=00347-0… - Herbert Jaeger -- Dr. Herbert Jaeger Professor of Computing in Cognitive Materials Rijksuniversiteit Groningen Faculty of Science and Engineering - CogniGron Bernoulliborg Nijenborgh 9, 9747 AG Groningen office: Bernoulliborg 402 phone: +31 (0) 631 921588 COVID home office phone: +49 (0) 4209 930403 web: www.ai.rug.nl/minds/

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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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