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Call for abstracts 'Neuromorphic, Natural and Physical Computing: Interdisciplinary Foundations (NNPC 2023)”, 25th – 27th of October 2023 in Hanover, Herrenhausen castle - Germany

by Prof. Dr. Gordon Pipa

We are happy announce the “Neuromorphic, Natural and Physical Computing: Interdisciplinary Foundations (NNPC 2023)”, taking place from 25th – 27th of October 2023 in Hanover, Herrenhausen castle. Please see our website for information https://nnpc-conference.com/ . The general aim of the conference is to boost interdisciplinary transfer of ideas and networking in the wider fields of non-digital computing. NNPC 2023 is a successor to the 2018 conference “Cognitive Computing: Merging Concepts with Hardware” (https://nnpc-conference.com/2018/ ) whose very productive and motivating format will be kept. The event is generously supported by the Volkswagen Foundation. The conference will run in 5 single-track sessions. 1. Theory: new concepts and mathematical foundations, 2. Physical substrates: materials, devices, micro-architectures, 3. Guides from nature: neuroscience, theoretical biology, complex systems, 4. Scaling up: modular architectures, complex data structures and processes, 5. Applications: demonstrators, use-cases, user interfacing, hybrid solutions. To ensure maximum participation, all attendees are required to submit a 2-page abstract on a subject relating to one of the session themes. These abstracts are peer-reviewed. All accepted submissions will be granted an oral or poster presentation slot, and hosted publicly on the conference website upon agreement by the authors. Importantly, novelty is not essential as our aim is to make knowledge to diffuse across boundaries of the scientific domains involved. You find more detailed information about the aims, background, and thematic structure of this event in the Appendix. The submission form will be available on the conference website shortly. • Submission deadline: March 15th 2023. • Notify authors of acceptance: April 30th 2023. • Notify authors of type of contribution: May 14th 2023. We look forward to hearing from you and to meet in person to make NNPC 2023 a memorable success. With best regards, the Conference Chairs Conference Chairs: Daniel Brunner (photonics, neuromorphic architectures; CNRS) Gordon Pipa (neuroinformatics and cognitive computing; University of Osnabrück) Damien Querlioz (Bioinspired Nanolectronics; Université Paris-Saclay France) Susan Stepney (unconventional computing; University of York, UK) Financial chair: Herbert Jaeger (machine learning, nonlinear dynamics; University of Groningen) Appendix: Aims, structure, venue, and funding of the conference Overview of aims and structure. Four years ago, the pioneering conference Cognitive Computing: Merging Concepts with Hardware assembled a wide-spanning multidisciplinary audience to share and merge insights about non-standard concepts and technologies of computing. At least four traditions were brought together: • Neuromorphic computing: “learn from the brain” • Natural computing: “look at nature’s complex systems” • Physical computing: “use physical effects directly” • Non-standard theoretical computer science: “think outside the Turing machine” Work in these fields has enormously picked up speed in the interim, but it is still a plurality of traditions carried by a multitude of communities. We still lack unified concepts, shared terminology, transferable methods and common goals. After four years, it is a good time to take stock of progress that has been made, and to re-invigorate the effort of connecting our dispersed findings into a joint vision. We do not yet know how we will ultimately name our emerging field of generalized “computing” science. For the time being we will refer to it by calling out its main traditional anchors: Neuromorphic, Natural and Physical Computing (NNPC). In five sessions with much breakout times for personal exchange, we will explore 1. Theory: new concepts and mathematical foundations, 2. Physical substrates: materials, devices, micro-architectures, 3. Guides from nature: neuroscience, theoretical biology, complex systems, 4. Scaling up: modular architectures, complex data structures and processes, 5. Applications: demonstrators, use-cases, user interfacing, hybrid solutions. Each session will be commenced by a 1-hour invited keynotes and feature three 30-minute oral presentations selected from the submitted abstracts. In addition we will invite three 1-hour plenary lectures that cross the session themes. This leaves much time for breaks and extensive poster sessions, a condition that will be creating a productive atmosphere for personal networking. Here are the specifics of the five sessions: Session 1. Theory: new concepts and mathematical foundations. The physical substrates of NNPC will host dynamical phenomena that defy the principles of digital computing. Instead of relying on reproducible, stable binary switching, NNPC exploits dynamical processes that are stochastic, non-stationary, continuous-valued, un-clocked and spatially distributed. In order to enable a systematic, insightful design of NNPC systems, new conceptual frameworks and mathematical formalisms are needed. Suggestive topics: • Representing symbols, discrete data structures and operations in nonlinear dynamics • Non-Shannon definitions and measures of information • Emergent phenomena in collective dynamics • Nanoscale or collective phenomena which can serve as computational primitives • Entrainment of NNPC system dynamics to input streams • Temporally and spatially multiscale modeling of complex dynamics • Stabilization and self-calibration mechanisms • Life-long change: aging, continual learning, adaptation to changing tasks and environments • Adaptations of classical (deep) neural network architectures and algorithms to NNPC hardware • Integrative formal languages which unify selected aspects across, for example, stochastic processes, information theory, nonlinear dynamics, topology and graph theory, algebra or signals, systems and control • New kinds of formal logics to capture semantics of NNPC processes • Analyses of ultimate energy minimization or information density • Fundamental models of NNPC systems, analog to the Turing machine model for digital computing Session 2. Physical substrates: materials, devices, micro-architectures. Biological brains are so efficient because evolution has found ways to exploit a host of physiological and physical effects which neuronal tissue can offer. Extending this idea of “exploiting the physics” beyond brains, the strategy of what has been called “physical computing” or “in-materio computing” is to find ways to exploit for NNPC whatever physics can offer, opening up for effects that are inaccessible to neurophysiological substrates (and accessible to engineering and fabrication). Suggestive topics: • Physical phenomena supporting computing provided by nano- or microscale devices, across physical domains (electronic, photonic, spintronic, mechanic, chemical, etc.) • Exploiting quantum effects in other ways than in classical quantum computing (e.g. quantum reservoirs) • Spatial structuring in thin films or 3D substrates, boundary formation • Nano- or microscale phase transitions and percolation • Small-scale physical structures with heterogeneous or self-organizing phase-change materials • Non-wire-bound information transfer in physical media through diffusion, fields, soliton or wave propagation, or mechanical transmission • Novel devices with non-digital, modulatable input-output transfer functions • Phenomena and devices with slow-fast dynamics where the slow dynamics can be used for learning or adaptation • Analyses and characterization of computationally potentially relevant properties of materials and devices • Development of “practically useful” materials and devices: long endurance, operation at room temperature, fabricability • Functional ensembles of novel devices in the spirit of neural microcircuits or elementary integrated circuits • Progress in currently investigated neuromorphic architectures (memristor crossbars, spike routing, analog neuron and synapse circuits) Session 3. Guides from nature: neuroscience, theoretical biology, complex systems. Biological brains are currently cited as the living proof that highly energy-efficient and “cognitive” computing beyond the limits of the digital paradigm are possible. This has led to the current dominance of the term “neuromorphic” when one wants to point to alternative computing technologies. However, there is also a long tradition of other non-digital computing proposals, which have been referred to by names like natural / physical / unconventional computing, and which have been pursued in various niches of CS, AI, Alife, theoretical physics and biology, and elsewhere. Our conference gives a forum for all alternative computing paradigms, neuromorphic and other sorts of “unconventional”. Suggested topics: • Learning from the brain: neuro-computational principles, circuits, architectures, and control flows: the neural engineering framework, neural field theory, neural sampling and others • Current developments in DNA computing, swarm intelligence, fungus computing, pattern theory, stochastic and hyperdimensional computing, membrane computing, immune systems, reservoir computing and others • Neuro-plausible learning and optimization concepts, potentially leveraging self-organization and enabling features like continuous learning, learning without forgetting • How do humans / animals build their world models? • Strategies from nature for system robustness (theoretical biology, neuroscience, ecology) • Pre-rational intelligence in animals from amoeba to insects to pigeons, zebra finches and rats (and the pre-rational information processing in humans, too) • Computational interpretations of self-organization in complex natural systems • ALife views on computing systems Session 4. Scaling up: modular architectures, complex data structures and processes. A key factor that empowered digital computing to become a world-changing technology is its scalability. Starting from concatenating bits into bitstrings and Boolean gates into Boolean circuits, arbitrarily compounded hierarchical data structures and program flows can be designed according to well-understood compositional principles. General principles of compositionality for non-symbolic information representations and arbitrarily extensible processing hierarchies for NNPC await their discovery. On the hardware side, only a few proposals for extensible multi-module neuromorphic architectures have been proposed (SpiNNaker immediately comes to mind) which present technical solutions for neural signal routing but are still limited with regards to functional and architectural diversity of the joinable modules. From a use case view, compositional principles for NNPC task specifications are likewise still restricted to specific, limited computational paradigms (as in the neural engineering framework or Act-R). Progress in general principles for scaling systems to arbitrary complexity is a key condition for the long-term sustainability of NNPC. Suggested topics: • Concepts for compositional non-symbolic “data” and information representation • Concepts for compositional procedure hierarchies • Synchronization mechanisms in unclocked parallel computing systems • Cognitive architectures, hierarchical control principles, autonomous agent models • Configuration principles for multi-module neural network architectures • Bidirectional top-down and bottom-up processing in deep neural (and other) architectures • Unclocked FPGA demonstrations • Routing and addressing mechanisms – formal and in hardware • Fundamental questions of hardware topology and physical integration to enable scalability of resources (energy, space, heat deposition, etc.) • High-capacity, richly structured long-term memory • Lifelong learning in NNPC systems • Growing hardware systems • Multi-modal sensor signal processing in non-digital neuromorphic systems • Progress in large-scale neuromorphic systems • Distributed energy supply in NNPC systems • Distributed input and output channeling to/from NNPC systems • NNPC-suited communication formats and networking solutions • Deep spiking neural networks and multi-module recurrent neural networks suitable for analog hardware realizations • Options and limits of commercial fabricability • Hybrid digital-NNPC systems aiming for scalable complexity Session 5. Applications: demonstrators, use-cases, user interfacing, hybrid solutions. Commercially or societally relevant scenarios for NNPC applications are still confined to niches. This is certainly due, on the one hand, to the early stage of NNPC research which is still mostly foundational and academic. But on the other hand, in our search for broad application scenarios we might be partly blinded by the urge to replace digital solutions in order to outwit the “End of Moore’s Law” and save energy. While this original motivation will remain strong and continue to call for NNPC solutions, other NNPC systems may turn out to be so different from digital systems that they cannot simply be plugged in where the latter are to be phased out. To the extent that NNPC systems become more brain-like (self-organizing, aging, with individual learning histories) they also become less computer-like. They may not be programmable in the accustomed way but need to be trained; they may not be identically reproducible but individual; they may not be re-bootable from some starting state but always-on (and might “die” if cut from energy supply). On the plus side, besides their energy efficiency they may boast an admirable robustness against variable or noisy input and physical damage; realize enormous data throughput rates; be bio-implantable; find creative un-premediated solutions for their tasks, and last but not least they may be un-hackable due to their individuality. All of this requires a thorough re-thinking of what an information-processing system is, what it can be used for, or what it can be doing all on its own. This is an interdisciplinary agenda which involves not only engineers but also psychologists, sociologists, economists and philosophers. Suggested topics: • Progress in currently discussed application scenarios: optical computing for communication systems, implantable neurochips and neuroprosthetics, ultra-low power or even energy harvesting edge computing, sensing and control for compliant or soft robots, analog/spiking adaptations of deep learning techniques, ubiquitous sensing, and more. • Methods to “make NNPC systems do what we want”: generalized concepts of “programming”, physical and functional configuration methods, training and scaffolding schemes, evolutionary optimization • Engineering pipelines: how would they differ from the digital system development routines? • How to “use” intelligent autonomous agents (avatars, game characters, robots) • Explainable NNPC: from formal analyses of trained distributed systems to accountability ethics of autonomous, individual artificial agents • Philosophy of engineering: a concept shift from reproducible, controllable tools to individual agents and personal companions • Interdisciplinary education: academic study programs, web services, funding initiatives Conference venue. The venue, the Castle of Herrenhausen (https://www.schloss-herrenhausen.de/en/home/ ), a heritage of the Kings of Hannover – who for a long historical period were at the same time Kings of England – was transformed into an award-winning center for scientific events and is today administered and maintained through the Volkswagen Foundation. The Herrenhausen Gardens stretch across hectares of classical French gardening. Why the Volkswagen Foundation supports NNPC. All funding is provided by the Volkswagen Foundation (https://www.volkswagenstiftung.de/en ), Germany’s largest private organization for the advancement of scientific research. The funding covers the royal conference venue, excellent catering, travel and accommodation for all speakers and the session chairs, and fee waivers for every participant. There is a reason for this generous commitment. The Foundation focuses its investments on a small number of research fields across all sciences that are (i) interdisciplinary and in a nascent stadium, (ii) not yet widely funded by industry or public agencies, (iii) show a potential for foundational discoveries and long-term societal benefits. One of these foci identified by the Foundation coincides with the themes of NNPC: non-digital computing technologies, including but not limited to neuromorphic computing, across all levels from materials through devices, microchip technologies, new computing paradigms, user-machine interaction scenarios, to the philosophy of computing and societal impact. The 2018 conference “Cognitive Computing” was a trigger for the Foundation to adopt this theme. Within this theme, the Foundation supports a spectrum of activities, among them our 2023 conference.

Feb. 24, 2023

Postdoctoral positions in learning and pain modulation, NIH

by Atlas, Lauren (NIH/NCCIH) [E]

Dr. Lauren Atlas’s laboratory<https://www.nccih.nih.gov/research/intramural/section-on-affective-neurosci…> is recruiting one to two postdoctoral researchers with expertise in fMRI and affective science to join the Section on Affective Neuroscience and Pain (ANP) to lead new projects on the psychological modulation of pain and emotional experience. Dr. Atlas’s lab is part of the National Center for Complementary and Integrative Health’s (NCCIH) intramural research program<https://www.nccih.nih.gov/research/intramural>, and affiliated with the Intramural Research Programs of the National Institute of Mental Health (NIMH) and National Institute on Drug Abuse (NIDA). Learn more about the NIH Intramural Training Program.<https://www.training.nih.gov/programs> Research in the ANP Lab focuses on the mechanisms by which expectations, learning, and other cognitive and affective factors influence pain, emotion, and clinical outcomes. We combine approaches from experimental psychology, neuroimaging, psychophysiology, and computational modeling to investigate pain and emotional experience in healthy individuals as well as individuals with chronic pain and/or affective disorders. We are particularly interested in the intersection of appetitive and aversive learning, how psychosocial factors influence pain and clinical outcomes, and questions motivated by pain’s central role in the opioid crisis. Postdoctoral researchers are expected to develop their own projects, with guidance, and to collaborate with other researchers in the lab as well as in the broader NIH community. We are looking for someone to spearhead new projects using high field imaging (7T-FMRI) to examine pain and perception across domains and/or using simultaneous PET-MRI to study the role of dopamine and opioids in pain modulation. Clinical collaborations to look at the intersection between pain, mental health, and/or substance use disorders are also possible. The candidate should have a strong background in psychology and neuroscience and must have received a Ph.D. in a relevant field by the time of appointment. Candidates with successful publications in the fields of pain, emotion, and/or computational modeling are encouraged to apply. Postdoctoral positions require experience with 1) design of behavioral and fMRI experiments, 2) analysis of fMRI data using statistical parametric mapping packages (SPM, AFNI, etc.), and 3) programming and analysis skills in MATLAB, R, and/or Python. These requirements will be flexible for candidates with clinical experience or experience in psychopharmacology, as we are currently planning clinical collaborations. Appointments and salary are commensurate with research experience and accomplishments (www.training.nih.gov/programs/postdoc_irp<http://www.training.nih.gov/programs/postdoc_irp>). The candidate will be supported with the excellent intramural NIH fellowship in a stimulating and interactive research environment at NIH. NIH has exceptional multidisciplinary research facilities including structural and functional MRI, MEG, PET, and TMS. Our lab is fully funded with dedicated weekly scan time, a full-time data analyst, and the opportunity to work alongside some of the world’s foremost fMRI experts. Training in advanced imaging and other techniques is available, as are courses in grant writing and career development. Trainees can also apply to be fellows in the Center on Compulsive Behaviors<https://research.ninds.nih.gov/researchers/center-compulsive-behaviors-ccb#….>, a trans-NIH fellowship program. This is an exciting and collaborative environment for those interested in pursuing a career in clinical or cognitive neuroscience. How To Apply Applicants should submit a CV, a brief description of research interests and career goals, and the names of three references to Dr. Lauren Atlas<mailto:lauren.atlas@nih.gov> (Investigator/Chief, Section on Affective Neuroscience and Pain, NCCIH/NIMH/NIDA, NIH). Applications will be reviewed on a rolling basis. Applications will be accepted until the position is filled. The Department of Health and Human Services and NIH are equal opportunity employers committed to equity, diversity, and inclusion.

Feb. 23, 2023

Call for contribution and registration to the Systems Vision Science Symposium: Aug. 22-24, 2023, in Tuebingen, Germany

by Pavlovic, Maria

Systems Vision Science Symposium Aug. 22-24, 2023 in Tübingen, Germany Our symposium takes place at the end of our Systems Vision Science summer school Aug. 14-24, 2023. Presentation topics by the invited speakers will be ® Topics in Systems Vision Science ® The power of two: New perspectives on binocular vision ® Central versus peripheral vision We are pleased to announce our symposium's keynote speaker: Marty Sereno. The keynote speech will be on August 22, 2023 Invited speakers of the Systems Vision Science Summer School and Symposium include: Assaf Breska, Peter Dayan, Andrea van Doorn, Wolfgang Einhäuser-Treyer, Karl Gegenfurtner, Ziad Hafed, Tadashi Isa, Jan Koenderink, Kristine Krug, Hanspeter Mallot, Laurence Maloney, Pascal Mamassian, Antje Nuthmann, Daniel Osorio, Andrew Parker, Jenny Read, Alexander Schütz, Manuel Spitschan, Kristina Visscher, Li Zhaoping. -------------------------------- We invite you to submit contributions in form of posters to the symposium on all topics in Systems Vision Science, which combines computational, behavioral, and neuroscience methods to discover functions and algorithms for vision in various brain regions and their implementations in neural circuits. To maximize exchanges during the symposium, each poster will be displayed throughout the symposium, which includes five poster sessions (two daytime sessions and three evening sessions), in a venue next to the lecture hall and coffee breaks to give enough time for discussions, networking and knowledge exchange. To contribute, please fill out our registration form including an abstract, which can be found here: <https://summerschool.lizhaoping.org/contributions-for-symposium/> https://summerschool.lizhaoping.org/contributions-for-symposium/ -------------------------------- Submissions of contributions are possible until April 30, 2023. Registration without contribution to the symposium will be open until capacity or deadline for organization is reached. This years venue capacity is 100, including invited speakers and summer school participants. Information about our summer school, which takes place just before the Systems Vision Science Symposium, can be found here: <https://summerschool.lizhaoping.org/> https://summerschool.lizhaoping.org/ Please direct inquiries to <mailto:svs.summerschool@tue.mpg.de> svs.summerschool(a)tue.mpg.de -------------------------------- Organizing team: Li Zhaoping Ulf Lüder Maria Pavlovic Junhao Liang Max Planck Institute for Biological Cybernetics University of Tuebingen www.lizhaoping.org <http://www.lizhaoping.org>

Feb. 23, 2023

Research Associate on project “A technology to extract memories from the human brain”

by Howard Bowman

POSTDOC RESEARCH ASSOCIATE ON PROJECT “A TECHNOLOGY TO EXTRACT MEMORIES FROM THE HUMAN BRAIN USING EFIT6 AND THE FRINGE-P3 BRAINWAVE METHOD” School of Psychology and Centre for Human Brain Health, University of Birmingham, UK. We are looking for a researcher with neuroimaging and machine learning expertise. The Fringe-P3 method (Bowman et al, 2013; Alsufyani et al, 2019) developed out of a line of theoretical work focussed on temporal attention and perception on the fringe of awareness (Bowman & Wyble, 2007; Avilés et al, 2020; Bowman & Avilés, 2022). The method provides a means to present a large number of visual stimuli very rapidly to a participant’s brain and then determine with EEG, which of those stimuli the participant finds salient. A very simple form of salience that we look at is familiarity, with stimuli that are familiar breaking into participants’ awareness and thereby generating a P3 (or a variant of it), which we detect with EEG. The method has been proposed as a deception detector, specifically, a (countermeasures-resistant) concealed-knowledge test (Bowman et al, 2013, 2014; Alsufyani et al, 2019; Harris et al, 2021). Our recent Innovate UK project with the company Visionmetric (https://visionmetric.com/) used the Fringe-P3 method to provide a prototype system for extracting the memory of a face. This is done by generating a facial morph that is a weighted average of the faces presented in rapid serial visual presentation, with weight determined by the strength of the P3 that face generated. A demo of the system developed in this project can be seen here: https://www.cs.kent.ac.uk/people/staff/hb5/EEGFIT_prototype_demo_cut.mp4 The Research Associate will be employed on a recently awarded EPSRC Impact Acceleration account at the University of Birmingham, which, with Visionmetric, will improve the efficiency with which P3s are detected with machine learning and will also explore alternative detection modalities, such as pupil dilation. The position is for one year in the first instance, but with the possibility of follow-on funding. Direct enquiries to the Principal Investigator, Howard Bowman (H.Bowman(a)bham.ac.uk<mailto:H.Bowman@bham.ac.uk>). Professor Howard Bowman (Psychology, University of Birmingham; Computing, University of Kent and Wellcome Centre for Human Neuroimaging, UCL [honorary]). To apply for this job, search for it on the following site, https://edzz.fa.em3.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_6… Alsufyani, A., Hajilou, O., Zoumpoulaki, A., Filetti, M., Alsufyani, H., Solomon, C. J., ... & Bowman, H. (2019). Breakthrough percepts of famous faces. Psychophysiology, 56(1). Avilés, A., Bowman, H., & Wyble, B. (2020). On the limits of evidence accumulation of the preconscious percept. Cognition, 195, 104080. Bowman, H., & Avilés, A. (2022). No Subliminal Memory for Spaced Repeated Images in Rapid-Serial-Visual-Presentation Streams. Psychological Science, 33(11), 1959-1965. Bowman, H., Filetti, M., Janssen, D., Su, L., Alsufyani, A., & Wyble, B. (2013). Subliminal salience search illustrated: EEG identity and deception detection on the fringe of awareness. PLoS One, 8(1). Bowman, H., Filetti, M., Alsufyani, A., Janssen, D., & Su, L. (2014). Countering countermeasures: Detecting identity lies by detecting conscious breakthrough. PloS one, 9(3), e90595. Bowman, H., & Wyble, B. (2007). The simultaneous type, serial token model of temporal attention and working memory. Psychological review, 114(1), 38. Harris, K., Miller, C., Jose, B., Beech, A., Woodhams, J., & Bowman, H. (2021). Breakthrough percepts of online identity: Detecting recognition of email addresses on the fringe of awareness. European Journal of Neuroscience, 53(3), 895-901. -------------------------------------------- Professor Howard Bowman (PhD) Professor of Cognition & Logic in Computing at Uni Kent, and Professor of Cognitive Neuroscience in Psychology at Uni Birmingham (honorary at Wellcome Centre for Human Neuroimaging, University College London) Centre for Cognitive Neuroscience and Cognitive Systems and the School of Computing, University of Kent at Canterbury, Canterbury, Kent, CT2 7NF, UK email: H.Bowman(a)kent.ac.uk<mailto:H.Bowman@kent.ac.uk> WWW: http://www.cs.kent.ac.uk/people/staff/hb5/ School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK

Feb. 23, 2023

Open rank faculty positions at the intersection of biological and artificial intelligence at Indiana University

by Zoran Tiganj

The Luddy School of Informatics, Computing, and Engineering (SICE), the Department of Psychological & Brain Sciences (PBS), and the School of Optometry (IUSO) at Indiana University (IU) Bloomington invite applications for two faculty positions to begin on August 1, 2023. We seek applicants working at the intersection of biological and artificial intelligence, with a focus on reverse engineering the computational foundations of biological intelligence using tools from machine learning and artificial intelligence. The positions are part of a new initiative—Reverse Engineering the Foundations of Intelligence—that aims to transform our understanding of human and animal intelligence. IU has long been an international leader in discussions of how brains, bodies, and environments contribute to intelligent behavior. This initiative is designed to build on these strengths and propel IU to the forefront of research at the interaction of biological and artificial intelligence. The positions are open at the full and associate professor levels, but exceptional candidates at the assistant professor level or in industry may be considered. We seek dynamic individuals with an international reputation and experience working in rapidly expanding & intellectually diverse interdisciplinary areas. We also seek individuals who excel working in team environments and whose research, teaching, and service will contribute to IU’s commitment to diversity, equity, and inclusion. Minimum Qualifications: A PhD in psychology, neuroscience, cognitive science, computer science, or a related field, and a distinguished record of scholarship, teaching, and professional experience appropriate for a tenured professorship at IU Bloomington. Applications received by March 2, 2023 will receive full consideration; however, the search will remain open until suitable candidates are found. Review of applications will begin immediately and continue until the positions are filled. Candidates should review application requirements, learn more about SICE, PBS, IUSO, and employee benefits, and apply online at: https://indiana.peopleadmin.com/postings/16752 Questions, nominations, and confidential inquiries may be sent to Justin Wood (woodjn(a)indiana.edu) or Rowan Candy (rcandy(a)indiana.edu) Indiana University is an equal employment and affirmative action employer and a provider of ADA services. All qualified applicants will receive consideration for employment based on individual qualifications. Indiana University prohibits discrimination based on age, ethnicity, color, race, religion, sex, sexual orientation, gender identity or expression, genetic information, marital status, national origin, disability status or protected veteran status. Before a conditional offer of employment with tenure is finalized, candidates will be asked to disclose any pending investigations or previous findings of sexual or professional misconduct. They will also be required to authorize an inquiry by Indiana University Bloomington with all current and former employers along these lines. The relevance of information disclosed or ascertained in the context of this process to a candidate’s eligibility for hire will be evaluated by Indiana University Bloomington on a case-by-case basis. Applicants should be aware, however, that Indiana University Bloomington takes the matters of sexual and professional misconduct very seriously.

Feb. 22, 2023

Postdoctoral opportunity in Janssen Pharmaceuticals

by Rouhollah Abdollahi

We have a great opportunity for postdoctoral position in our team in Janssen pharmaceuticals, companies of Johnson & Johnson, working on neuroimaging projects. The location of the candidate should be Europe or USA, but remote option also can be arranged. https://jobs.jnj.com/en/jobs/2306106495w/post-doctoral-scientist-data-scien… -- Sent from Gmail Mobile

Feb. 21, 2023

Software Highlight: Kay Robbins: HED (Hierarchical Event Descriptors)

by Ankur Sinha

Dear all, Apologies for the cross-posts. Please join the INCF/OCNS Software Working Group for our next Software Highlight session: Kay Robbins[0] will introduce and discuss HED, a practical system for describing an experiment using an analysis-ready framework. https://ocns.github.io/SoftwareWG/2023/02/17/software-highlight-kay-robbins… - Date: February 28, 2023, 1600 UTC (Click here to see your local time[1]) (Add to calendar[2]). - Zoom (link): https://ucl.zoom.us/j/99321986413?pwd=OUdFTlJ3NVloUmJ1U0Q3WE9vRERMZz09 The abstract for the talk is below: In human neuroimaging experiments, a record of what a participant experiences together with a clear understanding of the participant (task) intent are key to interpreting recorded brain dynamics. HED (Hierarchical Event Descriptors, https://www.hedtags.org) annotations and supporting infrastructure can provide human-understandable machine-actionable descriptions of events experienced during laboratory and/or real-world time series recordings. HED, which is well-integrated into BIDS (Brain Imaging Data Structure) has an ecosystem of tools supporting researchers at various stages including data acquisition, annotation, sharing, and analysis. This talk will describe HED principles, focusing on basic representations of an experiment and its design. Various tools in the HED ecosystem to support search, summary and analysis will be introduced and demonstrated. Finally, we’ll discuss how tool developers can leverage the HED infrastructure to build advanced analysis tools capable of automated analysis in support of machine learning. HED is an entirely open-source project, and the HED Working Group welcomes contributors and contributions. Papers and resources: - Capturing the nature of events and event context using Hierarchical Event Descriptors (HED). NeuroImage. https://www.sciencedirect.com/science/article/pii/S1053811921010387 - Building FAIR functionality: Annotating events in time series data using Hierarchical Event Descriptors (HED). Neuroinformatics. https://link.springer.com/article/10.1007/s12021-021-09537-4 - Resources: https://www.hed-resources.org - GitHub organization: https://github.com/hed-standard [0] https://www.utsa.edu/sciences/computer-science/faculty/KayRobbins.html [1] https://www.timeanddate.com/worldclock/fixedtime.html?msg=Software+Highligh… [2] https://ocns.github.io/SoftwareWG/extras/ics/20230228-kay-robbins-hed.ics On behalf of the Software WG, -- 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

Feb. 21, 2023

PhD position in System Neuroscience

by Shahidi, Neda

Dear all, I have a new Ph.D. position in System Neuroscience at the University of Göttingen and the German Primate Center in Göttingen. We will use a new paradigm in studying neural correlates of decision-making in monkeys: The animals in our study will make decisions that are more natural to them, less repetitive, and require less training. Also, we will use chronic electrophysiology enabling us to simultaneously probe many neurons using a technology that is more or less plug-and-play. That means less animal training and less neuron-fishing. However, because there is nothing like a free lunch, this comes with a cost: Analyzing the data will be way more complicated, compared to a classical experiment! Therefore, the ideal candidate is proficient in data analysis and coding, but also enthusiastic to work with monkeys (Do you enjoy teaching your dog a trick or two? then you will also enjoy working with our monkeys). Please find more information here: https://www.uni-goettingen.de/en/644546.html?filters={%22vollzeit%22:[],%22…<https://www.uni-goettingen.de/en/644546.html?filters=%7B%22vollzeit%22:%5B%…> and please feel free to spread the word. Kind Regards Neda

Feb. 21, 2023

MBL Methods in Computational Neuroscience Course

by Stephen A. Baccus

Applications are open for the Methods in Computational Neurosciencecourse at the Marine Biology Laboratory in Woods Hole, MA. The course will run from July 26 to August 23, 2023. The online application form and additional information can be found at: https://www.mbl.edu/education/advanced-research-training-courses/course-off… The course application deadline is *March 31*. The course covers a range of topics in computational neuroscience including neuronal biophysics, neural coding & information processing, circuit dynamics, learning & memory, motor control, and cognitive processing & disease. In addition, numerous tutorials and problem sets will cover a broad range of computational and mathematical modeling methods. The course strongly emphasizes the collaboration between theory and experiment in solving neuroscience problems, and lectures will be given by a mixture of theorists and experimentalists. The final weeks of the course are primarily reserved for work on projects that students design in collaboration with the resident faculty. 2023 Course Directors: Stephen Baccus, Stanford University Xiao Jing Wang, New York University 2023 Faculty: Larry Abbott, Columbia University Emery Brown, MIT Nicolas Brunel, Duke University Randy Buckner, Harvard University Anne Churchland, UCLA Claudia Clopath, Imp. College London Marlene Cohen, U. of Pittsburgh Shaul Druckmann, Stanford University Uri Eden, Boston University Bard Ermentrout, U. of Pittsburgh Adrienne Fairhall, U. of Washington Michale Fee, MIT Loren Frank, UCSF Stefano Fusi, Columbia University Surya Ganguli, Stanford University Paul Glimcher, New York University Mark Goldman, UC Davis Nancy Kopell, Boston University Eve Marder, Brandeis University John Murray, Yale University Srdjan Ostojic, ENS - PSL Yiota Poirazi, IMBB-FORTH David Redish, U. Minnesota Terry Sejnowski, Salk Institute Sebastian Seung, Princeton University Reza Shadmehr, Johns Hopkins Univ. Haim Sompolinsky, Hebrew University Nelson Spruston, Janelia Res., HHMI Nao Uchida, Harvard University Byron Yu, Carnegie Mellon University Greg Wayne, DeepMind

Feb. 20, 2023

Postdoc position in bio-inspired AI at University of Sussex

by Thomas Nowotny

Dear colleagues, We are looking for a post-doctoral research fellow to join our Sussex team working on bio-inspired AI and computational modelling of insect behaviour and learning. You will join a BBSRC funded project called “Emergent embodied cognition in shallow neural networks”. https://www.sussex.ac.uk/about/jobs/research-fellow-ref-10735 Your primary role will be to develop simulations of learning problems that insects face such as flower learning or navigation. Insect learning occurs rapidly within shallow neural networks. This is possible because learning is an active process emerging from the interaction of evolved brains, sensory systems and behaviours. We will explore how behavioural strategies and specialised sensors interact with learning success. You will work under the supervision of Prof Paul Graham (Sussex, School of Life Sciences) and Professors Andrew Philippides and Thomas Nowotny (Sussex, Department of Informatics). You will join an active team of research fellows and PhD students working on similar topics. Closing date: 09 March 2023. Applications must be received by midnight (UK) Expected interview date: to be confirmed Expected start date: early April 2023 Please contact Prof Paul Graham, p.r.graham(a)sussex.ac.uk, for informal enquiries. With regards, Thomas -- Prof. Thomas Nowotny Head of AI Research Group CCNR, Sussex Neuroscience Phone: +44-1273-678593 Engineering and Informatics, Fax: +44-1273-877873 University of Sussex, Falmer, Brighton BN1 9QJ sussex.ac.uk/informatics/tnowotny<http://sussex.ac.uk/informatics/tnowotny> [../../owa/redir.aspx?C=9e11bb0e527242938402b42d9b5498ea&URL=http%3a%2f%2fsussex.ac.uk%2finformatics%2ftnowotny] I support the University of Sussex Community Pledge, as I continue to help those around me during the pandemic. Small acts of collaboration, kindness and integrity can make a big difference. www.sussex.ac.uk/community-pledge<http://www.sussex.ac.uk/community-pledge>

Feb. 20, 2023