- Comp-neuro - lists.cnsorg.org

PhD Position, Moreno Lab, Comp Neuro, Barcelona
by Ruben Moreno Bote March 1, 2023

March 1, 2023

*PhD Position in* *Computational Neuroscience, Ruben Moreno-Bote Lab * *Center for Brain and Cognition, University Pompeu Fabra, Barcelona, Spain* 1 fully funded PhD position is available in the group of Theoretical and Cognitive Neuroscience of Ruben Moreno-Bote in the Center for Brain and Cognition at the University Pompeu Fabra, Barcelona, Spain. We are looking for excellent candidates with Physics, Mathematics or Machine Learning background interested in developing theory for the brain and mind and artificial intelligence. Knowledge of Computational Neuroscience or Neuroscience would be ideal, but it is not necessary. The candidate will develop state of the art theory and models of cognition and intelligence by using neural networks, reinforcement learning, machine learning, data analysis and multielectrode neural data. The main research topic of our lab is decision-making, from a multidisciplinary angle. The candidate will benefit from the stimulating environment of Barcelona area in Theoretical and Systems Neuroscience and will have the opportunity of enjoying a lively city. Our lab (https://www.upf.edu/web/tcn) forms part of a larger network of neuroscience labs in Barcelona. Financial support is provided by HHMI and the Spanish MINECO. APPLICATION: A full CV in pdf format and an extract of grades for degree and master studies should be sent to the following address: ruben.moreno(a)upf.edu DEADLINE: until the position is filled STARTING DATE: any time between September 2023 and January 2024 -- Rubén Moreno Bote Serra Húnter Professor and ICREA Academia Director of the Theoretical and Cognitive Neuroscience Group Center for Brain and Cognition & Dept. of Information and Communications Technologies University Pompeu Fabra Campus Ciutadella c\ Ramon Trias Fargas, 25-27 Mercè Rodoreda building, 3th floor (room 24.331) 08005 Barcelona, Spain https://www.upf.edu/web/tcn https://twitter.com/morenobote <https://twitter.com/morenobote?lang=ca>

1 0

PhD position in Natural Language Processing and Machine Learning at IT University of Copenhagen (deadline April 1st)
by Stefan Heinrich Feb. 28, 2023

Feb. 28, 2023

Full-time PhD position at IT University of Copenhagen, under the umbrella of the Pioneer Centre for AI, Denmark, starting in Summer-Autumn 2023. Topic: Modelling compositional language structures across languages. The origin of language development of human beings can at least be traced back to two sources: the survival needs for communication and the unique wiring of human brains. The two factors can co-develop with each other through life-span. Nevertheless, languages from the whole world are with tremendous diversity. Yet, given the fact that all human brains share very similar structures and connection patterns, which presumably afford for similar ways to encode and decode information from the external world, there likely exist some hidden common structures, like some word orders or numbers of phonemes in a language, that are shared at least within, or even across, language families. An important constraint for these similar structures comes from the theory that the brain is processing language embodied in all our senses and via processing streams that are also involved in a range of other cognitive functions from specific motor control up to general problem-solving. This suggests that language comprehension and production, in fact, developed on top of existing information processing schemes, which in turn might have similarly shaped how the different language families have developed. A particular mechanism that was recently hypothesized to give rise to the structure of the brain’s sequence processing is temporal compositionality and chunking, which seemingly operate on language sequences as well. With this PhD project, we want to identify and describe the specific, latent temporal encoding structures that may constrain the temporal features of spoken language. In this project, the candidate will study structure patterns in spoken language and investigate how to build a model that can extract temporal characteristics of speech across different languages. Since the project is interdisciplinary, active collaboration within the Pioneer Centre for AI, as well as with experts in computational neuroscience and developmental psychology in Germany and Japan are planned. Application details: The ideal candidate should have a Masters in Computer Science, Computational Neuroscience, Computational Linguistics, Developmental Psychology, Cognitive Science or related fields, as well as a strong interest in interdisciplinary research, at the intersection of Natural Language Processing, Machine Learning, and Psycholinguistics. The salary scale will be in accordance with the Ministry of Finance’s agreement with the Danish Confederation of Professional Associations for a full-time position. As a PhD Student at the Pioneer Centre for AI you will have extraordinary access to computing resources, international researchers across disciplines, courses and events at the centre and meaning collaboration with industry, the public sector etc. ITU is a teaching and research-based tertiary institution concerned with information technology (IT) and the opportunities it offers. The University offers an informal working environment, a varied everyday life, and a highly motivated, competent, diverse, and international faculty. Copenhagen has a strong educational system, a rich cultural life, universal healthcare, good childcare, and a well-functioning infrastructure. The city is also among the world’s most liveable cities according to the Economist Global Liveability Index. Candidates will work together with Stefan Heinrich (stehe(a)itu.dk) and Barbara Plank (bapl(a)itu.dk) and are encouraged to get in contact for details. Link to further application information: https://www.aicentre.dk/phd-openings - and application link: https://candidate.hr-manager.net/ApplicationInit.aspx?cid=119&ProjectId=181… Application deadline: 01 April 2023, at 23:59 CET. -- *************************** Dr. Stefan Heinrich Assistant Professor Computer Science Department IT University of Copenhagen https://stefanheinrich.net/ ***************************

1 0

Tenure-track position in computational neuroscience
by Asohan Amarasingham Feb. 28, 2023

Feb. 28, 2023

Dear Colleagues, The Department of Psychology at the City College of New York (CCNY) of the City University of New York (CUNY) is currently soliciting applications for a tenure-track assistant professorship in computational neuroscience. Review of applications will begin on March 3, 2023. Please consider submitting an application. Best regards, Asohan Amarasingham FACULTY VACANCY ANNOUNCEMENT The Department of Psychology at the City College of New York (CCNY) invites applications for a full-time, tenure-track faculty position in computational neuroscience at the rank of Assistant Professor to begin in Fall 2023. The CCNY Psychology Department is a vibrant, diverse department located in Harlem, serving over 2000 undergraduate majors, with master's programs in General Psychology and Mental Health Counseling, a doctoral program in Clinical Psychology, and is affiliated with Ph.D. programs in Psychology and Neuroscience at the CUNY Graduate Center. The ideal candidate will use an innovative combination of computational, data-analytic, and/or modeling techniques to better understand how the brain gives rise to cognitive phenomena. All areas of relevance to cognitive neuroscience are of interest, including but not limited to: sensation, perception, emotion, memory, language, learning and reward, and consciousness. Successful applicants will be encouraged to participate in all programs the Department offers and to pursue interdisciplinary collaborations within and across the program, the department, and other departments at the College, including the Grove School of Engineering, the CUNY School of Medicine, and many related programs at the CUNY Graduate Center, including the CUNY Advanced Science Research Center, the Initiative for Theoretical Sciences, and allied doctoral and master's programs that span the sciences. They will be responsible for teaching, research, and mentorship/advisement duties. They also will share responsibility for committee and department assignments including administrative, supervisory, and other functions. QUALIFICATIONS A Ph.D. in psychology, neuroscience, applied mathematics, computer science, engineering, or a similarly allied field is required. The candidate is expected to maintain an active program of research, publish theoretical and empirical research in top-tier journals, be committed to both undergraduate and graduate education, and provide mentoring/advisement to students. Potential for obtaining external grant support is essential. Also required is the ability to teach successfully, demonstrated scholarship or achievement, and the ability to cooperate with others for the good of the institution. COMPENSATION CUNY offers faculty a competitive compensation and benefits package covering health insurance, pension and retirement benefits, paid parental leave, and savings programs. We also provide mentoring and support for research, scholarship, and publication as part of our commitment to ongoing faculty professional development. HOW TO APPLY Only applications submitted through CUNYfirst will be considered for this position. If you are viewing this job posting externally, please apply as follows: * Go to www.cuny.edu <http://www.cuny.edu/> and click on "Employment" * Click "Search job listings" * Click on "More options to search for CUNY jobs" * Search for Job Opening ID number 25407 Click on the "Apply Now" button and follow the instructions. Applications, including the following must be uploaded to the CUNYfirst job application website as a single PDF document: 1. Cover Letter 2. Curriculum Vitae 3. Statement of research interest and goals 4. Selected Publications 5. Three (3) confidential letters of recommendation sent to kwok(a)ccny.cuny.edu<mailto:hkwok@ccny.cuny.edu>

1 0

NEST Conference 2023 – Save the date & registration
by Hans Ekkehard Plesser Feb. 27, 2023

Feb. 27, 2023

Dear Colleagues, The NEST Initiative is excited to invite everyone interested in Neural Simulation Technology and the NEST Simulator to the NEST Conference 2023. The NEST Conference provides an opportunity for the NEST Community to meet, exchange success stories, swap advice, learn about current developments in and around NEST spiking network simulation and its application. We particularly encourage young scientists to participate in the conference! This year's conference will take place as a virtual event on 15-16 June 2023. Register now! For more information please visit the conference website https://nest-simulator.org/conference We are looking forward to seeing you all in June! Hans Ekkehard Plesser and colleagues -- Prof. Dr. Hans Ekkehard Plesser Head, Department of Data Science Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

1 0

Call for applications - MSc Neuroscience, Uni Freiburg (Germany)
by Carsten Mehring Feb. 27, 2023

Feb. 27, 2023

MSc program in Neuroscience - University of Freiburg, Germany We are inviting applications for the interdisciplinary MSc program in Neuroscience at the University of Freiburg, Germany. The program provides theoretical and practical training in neuroscience, covering both the foundations and latest research in the field. It is taught by lecturers from an international scientific community from multiple faculties and neuroscience research centres. The modular course structure caters to the specific backgrounds and research interests of each individual student and we offer specialisations in neural circuits and behavior, computational neuroscience and neurotechnology. All courses are taught in English. We welcome applications with a background in natural sciences, mathematics, behavioural sciences, computer science, medicine or engineering sciences. The deadline for applications for the October 2023 entry is the 31st of March 2023. Further details can be found on our homepage http://www.mscneuro.uni-freiburg.de <http://www.mscneuro.uni-freiburg.de/> With kind regards Carsten Mehring — Bernstein Center Freiburg & Faculty of Biology University of Freiburg

1 0

post-doc position on interacting neuronal assemblies at University of Genova
by Paolo Massobrio Feb. 27, 2023

Feb. 27, 2023

We are seeking highly motivated candidates for a post-doctoral position (1 year) at the Neuroengineering and NeuroTechnology Lab, <http://www.unige.it/> University of Genova, Genova, ITALY. The candidate will be involved in the funded PNRR Italian Project Mnesys (https://mnesys.eu/) a large neuroscience and neuropharmacology consortium coordinated by University of Genova which involves 25 partners. Among the topics of the project, the one which will involve the candidate deals with both computational and experimental staffs. In particular, the candidate will work with experimental models of brain-on-a-chip where different neuronal populations (e.g., cortical-hippocampal; cortical-thalamic; cortical-cerebellar, .) interact originating complex neuronal dynamics. Depending on the candidate attitude, she/he will be involved in the development of large-scale computational models of such interconnected neuronal networks or the development of advanced algorithms to infer functional and dynamical properties originated by the interactions of these ensembles. Requirements: Candidates must have: 1) a PhD in bioengineering, computational neuroscience, physics, engineering, mathematics or a related field; 2) Excellent programming skills in Python, Matlab, C++/C#, 3) a published record of research in the field of computational neuroscience and/or neuroengineering; 4) experience in electrophysiological data analysis and/or modeling. Deadline for submitting the application is March 13th, 2023. The selected candidates will be contacted for a further interview during the following week. The earliest possible starting date is April 1st, 2023, and the position will last for 1 year (possible extension). Our research group has a long tradition in studying the interactions between neuronal populations coupling to Micro-Electrode Arrays (MEAs). See for example the following papers: 1. F. Callegari, M. Brofiga, P. Massobrio. Modeling the three-dimensional connectivity of in vitro cortical ensembles coupled to Micro-Electrode Arrays. PLoS Computational Biology, 2023. 2. M. Brofiga, M. Pisano, M. Tedesco, A. Boccaccio, P. Massobrio. Functional inhibitory connections modulate the electrophysiological activity patterns of cortical-hippocampal ensembles, Cerebral Cortex, 2022. 3. P. Massobrio, V. Pasquale, S. Martinoia. Self-organized criticality in cortical assemblies occurs in concurrent scale-free and small-world networks, Scientific Reports, 2015. 4. T. Kanagasabapathi, P. Massobrio, R. A. Barone, M. Tedesco, S. Martinoia, W. J. Wadman, M. M. J. Decre. Functional connectivity and dynamics of cortical-thalamic networks co-cultured in a dual compartment device. Journal of Neural Engineering, 2012. Our labs are located in Genova <https://www.visitgenoa.it/en/iat> , a beautiful town in northern Italy, both from historical (its historical center is the largest of Europe) and naturalistic point of view (sea and mountains coexist creating a unique landscape). Genova is only 1.30h away from Milan by train and connected by plane to Rome (1.00h), London (2h) and Paris (1.30h). Applications must include an extended CV, a motivation letter, the most relevant papers, and names and addresses of two references. If you are interested, please send your application to: Paolo Massobrio e-mail: paolo.massobrio(a)unige.it <mailto:paolo.massobrio@unige.it> Tel: +39-010-3352761 _________________________________ Paolo Massobrio, PhD Associate Professor of Bioengineering Neuroengineering and Neurotechnology Lab Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS) University of Genova Via Opera Pia 13, 16145, Genova, ITALY Phone: +39 010 3352761 URL: <http://www.dibris.unige.it/> www.dibris.unige.it E-mail: <mailto:paolo.massobrio@unige.it> paolo.massobrio(a)unige.it

1 0

Research Assoc Opening
by Yuvaraj Rajamanickam Feb. 27, 2023

Feb. 27, 2023

Hi Everyone, I hope you are all doing well! I am looking for a research associate for my project titled "Automated Boredom Detection using Multimodal Physiological Signals." If you could share the information with potential candidates, I would appreciate it. For more information, please refer to the job advertisement link. https://ntu.wd3.myworkdayjobs.com/Careers/job/NTU-Main-Campus-Singapore/Res… Regards YUVARAJ

1 0

LiSNN Seminar: Felix Effenberger - A biology-inspired recurrent oscillator network for computations in high-dimensional state space
by Tristan Manfred Stöber Feb. 24, 2023

Feb. 24, 2023

Dear friends and colleagues, as part of the Learning in Spiking Neural Networks Seminar Series are we cordially inviting you to the following presentation. Speaker: Felix Effenberger - Ernst Strüngmann Institute, Frankfurt am Main, Germany Title: A biology-inspired recurrent oscillator network for computations in high-dimensional state space Abstract: Biological neuronal networks have the propensity to oscillate. However, it is unclear whether these oscillations are a mere byproduct of neuronal interactions or serve computational purposes. Therefore, we implemented hallmark features of the cerebral cortex in recurrent neuronal networks (RNNs) simulated in silico and examined their performance on common pattern recognition tasks after training with a gradient-based learning rule. We find that by configuring network nodes as damped harmonic oscillators (DHOs), performance is substantially improved over non-oscillating architectures and that the introduction of heterogeneous nodes, conduction delays, and network modularity further improved performance. We furthermore provide a proof of concept of how unsupervised Hebbian learning can work in such networks. Analyses of network activity illustrate how the nonlinear dynamics of coupled DHOs drive performance, and provide plausible a posteriori explanations for a number of physiological phenomena whose function so far has been elusive. Also check out the corresponding preprint [1]. Time: 3rd of March 2023 at 14:00 Central European Time. Venue: Hybrid meeting, both on Zoom [2] and in person at the Frankfurt Institute for Advanced Studies, Ruth-Moufang-Straße 1, 60438 Frankfurt am Main, Lecture Hall 100. Best wishes in the name of the GRADE Initiative Learning in Spiking Neural Networks, Tristan Stöber Ps: Videos of previous events can be found on our youtube channel [3] [1] https://www.biorxiv.org/content/10.1101/2022.11.29.518360v1.abstract [2] https://ruhr-uni-bochum.zoom.us/my/tristanstoeber?pwd=YnZ2RlZVTUZPU2ZhNlFyR… [3] https://www.youtube.com/@lisnn.channel5458

1 0

Postdoctoral position in individual differences of plasticity in blindness (Washington DC)
by Ella Striem-Amit Feb. 24, 2023

Feb. 24, 2023

*Postdoctoral researcher position in individual differences of plasticity in blindness* The Sensory and Motor Plasticity Lab, led by Ella Striem-Amit, is currently recruiting a highly motivated and dedicated Postdoctoral researcher to join their team at Georgetown University in Washington DC, USA. The SAMP lab explores brain organization and experience-dependent plasticity by studying people born blind, deaf, or without hands, using behavioral and fMRI state-of-the-art analytical techniques. The successful applicant will work on the topic of individual differences in plasticity in people born blind. Specifically, the project will test how brain plasticity in blindness may manifest differently in different individuals, and how these differences may account for their compensatory skills and use of assistive devices. For more information about the lab, see samp-lab.facultysite.georgetown.edu <https://samp-lab.facultysite.georgetown.edu/research>. Excellent understanding of and experience with fMRI and data analysis are required. Strong programming skills (Matlab/R/python, etc.) are also a requirement. The position is not limited to US citizens. The start date is September-October 2023, but flexible in exceptional circumstances. This position is available for up to 4 years. To apply, please email your CV and a brief statement of research interests to Ella Striem-Amit (Ella.StriemAmit(a)georgetown.edu) with the subject line: “post-doc application”. Georgetown University is an Equal Opportunity/Affirmative Action Employer fully dedicated to achieving a diverse faculty and staff. All qualified applicants are encouraged to apply and receive consideration for employment without regard to race, color, religion, national origin, age, sex, disability status, protected veteran status, or any other characteristic protected by law. -- *Ella Striem-Amit (she/her)* Sensory and Motor Plasticity (SAMP) Lab Edwin H. Richard and Elisabeth Richard Assistant Professor Department of Neuroscience Georgetown University Medical Center 3970 Reservoir Rd., NW Washington, DC 20007 http://samp-lab.facultysite.georgetown.edu/

1 0

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 Feb. 24, 2023

Feb. 24, 2023

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.

1 0