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[jobs] Research Software Engineer, Nengo Neural Simulation Ecosystem
by Michael Furlong Oct. 26, 2026

Oct. 26, 2026

Research Associate — Research Software Engineer, Nengo Neural Simulation Ecosystem Centre for Theoretical Neuroscience, University of Waterloo · Posted 23 October 2026 Position summary The Centre for Theoretical Neuroscience is hiring a research software engineer on an 11-month term to modernize Nengo, our open-source neural simulation ecosystem. Nengo is a widely used spiking neural network simulator. The post is funded by a Research Software Maintenance Fund award from the Digital Research Alliance of Canada. The work is focussed on rebuilding continuous integration and test coverage, modernizing the OpenCL and deep-learning backends, returning the project to automated signed releases, and leaving documentation good enough for maintainers who did not write the code. About the project and team Nengo is a Python framework for building large-scale functional brain models, in continuous development since 2013. It has shipped 21 stable releases, records more than 270,000 downloads, and runs models across CPUs, GPUs and neuromorphic hardware including Intel Loihi and SpiNNaker. The ecosystem has outgrown its maintenance capacity. Several packages lag current Python, NumPy and GPU runtimes, continuous integration has gaps across the platform matrix, and one release sits unshipped behind completed dependency fixes. This post exists to solve these problems. You would report to Professor Chris Eliasmith and work alongside Terry Stewart and Michael Furlong of the National Research Council of Canada, who contribute code review and continuity. All work happens in public repositories through reviewed pull requests. Key responsibilities The funded work plan has seven packages. You would lead the technical work in all of them. * Testing and continuous integration. Rebuild CI across the supported platform matrix, raise automated test coverage, and add property-based tests for the numerical solvers. Establish performance and regression baselines so later improvements are measured rather than asserted. * Release engineering. Restore automated signed releases to PyPI and conda. Refresh packaging, dependency pinning and Python version support. Harden the build pipeline around credential handling and artefact signing. * GPU and accelerator backends. Update NengoOCL for current OpenCL runtimes, GPU drivers and Python versions. * Deep learning integration. Modernize NengoDL against current deep-learning runtimes. * Interactive interface. Broaden NengoGUI compatibility across current browsers, since it is the main entry point for new users. * Models and examples. Update the NengoZoo model and example collections. * Documentation. Consolidate user and maintainer documentation, update the maintainer handbook and contributor guide, record architecture decision records for the core abstractions, and publish machine-readable citation metadata with a versioned DOI per release. Alongside these, you would integrate software composition analysis and static analysis into CI, enable dependency vulnerability monitoring, and help publish a documented vulnerability disclosure procedure. Required qualifications * Training in computer science, engineering, neuroscience, physics, mathematics or a related field. PhD preferred. * Strong Python, with demonstrated fluency in the scientific stack, particularly NumPy and SciPy. * Demonstrated experience maintaining a non-trivial open-source project or research codebase: continuous integration, packaging, releases, issue triage and code review. * Working knowledge of at least one accelerator or deep-learning runtime, such as OpenCL, CUDA, PyTorch, TensorFlow or JAX. * Comfort working in public repositories through reviewed pull requests, with the code and the discussion visible. We are interested in evidence of what you have built and maintained. Preferred qualifications Prior use of Nengo or the Neural Engineering Framework, including through the Nengo Summer School. * Experience with neuromorphic hardware: Intel Loihi, SpiNNaker, BrainScaleS or FPGA targets. * Background in computational neuroscience, cognitive modelling or spiking neural networks. * Supply-chain and software security practice: dependency scanning, static analysis, artefact signing, vulnerability disclosure. * Full stack web development, for the NengoGUI work. * Technical writing for a developer audience, including API and architecture documentation. Terms of appointment Item Detail Classification Research Associate, University of Waterloo Term 11 months, non-renewable under this award Salary $110,000 for the full term Start date December 1, 2026, or as soon as possible thereafter Hours Full time, 1.0 FTE Location Waterloo, Ontario. Hybrid, with a strong preference for candidates who can work from campus regularly. Fully remote within Canada will be considered for an exceptional candidate. Unit Centre for Theoretical Neuroscience, University of Waterloo Supervisor Professor Chris Eliasmith The term is 11 months, which is a condition of the award. The appointment does not include pension participation or insured health benefits, which Waterloo extends to research appointments of one year or more; statutory benefits and vacation pay apply. We are reviewing applications as they arrive. How to apply Send the following to celiasmith(a)uwaterloo.ca, with the subject line "Nengo Research Associate Application": 1. A CV. 2. A link to code you have written or maintained, with one or two sentences on what your contribution was. A public repository, a package you maintain, or merged pull requests to someone else's project all work. 3. A short note, no more than a page, on how you meet the job requirements, and what you would tackle first and why. Applications are reviewed as they arrive and the posting closes when the position is filled. Required disclosures * Compensation. $110,000 for the 11-month term. There is no bonus, commission or other variable compensation attached to this position. * Vacancy status. This posting is for an existing vacancy, newly created by external research funding. * Artificial intelligence. Artificial intelligence is not used to screen, assess or select applicants for this position. * Canadian experience. Canadian work experience is not required. Applicants must be legally entitled to work in Canada by the start date. Applicants will be notified of the outcome within 45 days of their final interview. The University of Waterloo is committed to achieving barrier-free accessibility for persons with disabilities. Applicants who require accommodation during the recruitment process should contact the address above. The University regards equity and diversity as integral to academic excellence and encourages applications from all qualified candidates.

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CFP: FLAIRS40, Neural Network Special Track, St. Pete Beach, FL, May 24-27, 2027
by David B Oct. 26, 2026

Oct. 26, 2026

*Deadlines* Abstract Submission: January 22, 2027 Paper Submission: February 1, 2027 Paper Acceptance Notification: March 9, 2027 Camera Ready Version: April 5, 2027 *Call for Papers* The Florida Artificial Intelligence Research Symposium (FLAIRS) is a medium-sized interdisciplinary AI conference which is noted for its double- blind reviewing, free tutorials, and beautiful venues. This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas. Papers and contributions are encouraged for any work related to neural networks, data mining, or the intersection thereof. *Topics of interest may include (but are not limited to):* Applications such as Pattern Recognition, Applications, Generative AI methods and applications, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Power Systems, Signal Processing; Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cybersecurity, remote sensing, earth sciences, bioinformatics, and astronomy. Neural networks such as new developments in Deep Learning, Back Propagation, RBF, SVM, Ensemble Methods, Kernel Approaches; Hybrid approaches such as Neural Networks/Genetic Algorithms, Causal Nets trained with Backpropagation, Neural Network/Fuzzy Logic and Acceleration of neural network models via software or hardware. Other modeling algorithms such as hidden Markov models, decision trees, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches; graph modeling, pattern discovery, and anomaly detection; feature extraction and selection; post-processing techniques such as visualization, summarization, or trending; preprocessing and data reduction;and knowledge engineering or warehousing. *Submission Guidelines* Papers must follow the FLAIRS template guidelines ( https://www.flairs-40.info/call-for-papers) and be submitted as a PDF through the EasyChair conference system. (Do NOT use a fake name for your EasyChair login; your EasyChair account information is hidden from reviewers.) FLAIRS will not accept any paper which, at the time of submission, is under review for or has already been published or accepted for publication in a journal or another conference. Authors are also required not to submit their papers elsewhere during FLAIRS's review period. These restrictions apply only to journals and conferences, not to workshops and similar specialized presentations with a limited audience and without archival proceedings. Authors will be required to confirm that their submissions conform to these requirements at the time of submission. *Conference Proceedings* Papers will be refereed and all accepted papers will appear in the conference proceedings. *Track Co-chairs:* David Bisant, Central Security Svcs, bisant(a)umbc.edu Steven Gutstein, Booz Allen Hamilton, s.m.gutstein(a)gmail.com Lenin Mookiah, eBay, lenin.world(a)gmail.com *Program Committee Members:* Martin Atzmueller(University of Kassel, Germany) Lori Bogren (SomaLogic, USA) Ramesh Paudel (Sysco Corporation) Olac Fuentes (University of Texas at El Paso) Masoud Badiei Khuzani (eBay, USA) Tomasz Palczewski (SAP, USA) Chi Weng Cheong (PGIM, USA) Sergei Dolenko (M.V.Lomonosov Moscow State University, Russian Federation) Sheikh Rabiul Islam (University of Hartford, USA) Lawrence Holder (Washington State University, USA) Diane Cook (Washington State University, USA) Jacek Kukluk (Dana-Farber/Harvard Cancer Center, USA) Roberto Santana (University of Basque Country, Spain)

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2nd Workshop on Neuro for AI & AI for Neuro: Towards Multi-Modal Natural Intelligence
by Anton Arkhipov Oct. 25, 2026

Oct. 25, 2026

Dear Colleagues, Join us at the 2nd Workshop on Neuro for AI & AI for Neuro: Towards Multi-Modal Natural Intelligence! The Workshop will be held on February 22-23, 2027, alongside AAAI 2027 in Montreal, Canada. Call for Papers: https://neuroai-multimodal-workshop.github.io/. * Paper submission deadline: November 20, 2026 * Decision notification: December 5, 2026 * Short papers: Up to 4 pages (non-archival, excluding references) * Long papers: Up to 8 pages (archival, excluding references) * References and Supplementary: No page limit Building on the success of our first workshop at AAAI 2026 in Singapore, this edition will bring together researchers in AI, computational neuroscience, and neuromorphic engineering to explore how brain insights can inspire more adaptive, efficient, and robust AI systems, and how AI can deepen our understanding of neural computation. This year, we’ll place a special emphasis on context-dependent learning, continual adaptation in foundation models, and open-source benchmarks bridging neuroscience and AI. We look forward to bringing the community together again! Organizing team: Asim Iqbal, Shinya Ito, Reza Abbasi-Asl, Sophia Sanborn, Anton Arkhipov Anton Arkhipov Investigator [cid:2B7F5AD4-00BE-422F-8184-42BF1C16DEE3]

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2 PhD positions in translational computational neuroscience and NeuroAI at ICNS Hamburg, Germany
by Claus C. Hilgetag Oct. 25, 2026

Oct. 25, 2026

Dear colleagues, We invite applications for two PhD positions at the Institute of Computational Neuroscience (ICNS), University Medical Center Hamburg-Eppendorf (UKE), Germany: Translational computational neuroscience: Combining game theory, network neuroscience and computational modelling to investigate how brain regions and their interactions contribute to behaviour, impairment and recovery after stroke. The project will develop and validate approaches based on Multiperturbation Shapley value Analysis, in collaboration with project partners in Ghent, Paris and Amiens. Supervision by Claus Hilgetag. Details and application: UKE vacancy J000007015 <https://uke.jobs/index.php?ac=jobad&id=7015> Computational neuroscience and NeuroAI: Investigating how biological connectivity principles shape computation in recurrent neural networks and reservoir computing models. The project will explore characteristic bio-inspired network architectures for temporal and multimodal learning. Joint supervision by Fatemeh Hadaeghi and Claus Hilgetag. Details and application: UKE vacancy J000007013 <https://uke.jobs/index.php?ac=jobad&id=7013> We welcome applicants with a Master’s degree in computational neuroscience, computer science, physics, mathematics, biomedical engineering or related fields. Strong quantitative and programming skills, proficiency in Python, scientific initiative and fluent English are expected. Demonstrations of prior independent scientific achievements are an advantage. Both positions offer opportunities for independent research within an international, interdisciplinary group, with access to high-performance computing and support for conferences and training. Application deadline: 2 November 2026. Please apply through the respective UKE recruitment pages, which provide full requirements and application instructions. Please feel free to share this announcement with interested candidates. Best wishes, Claus C. Hilgetag Institute of Computational Neuroscience University Medical Center Hamburg-Eppendorf, Germany

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World wide VVTNS series (7th season): October 28 2026 | Circuit Mechanisms of Sensorimotor Learning in the Cortico-Basal Ganglia-Thalamocortical Network | Arthur Leblois CNRS, IMN Bordeaux, France
by David Hansel Oct. 25, 2026

Oct. 25, 2026

[image: VVTNS.png] https://www.wwtns.online <https://streaklinks.com/A9c7PbbpKY7PxB6PaAJWGD3-/https%3A%2F%2Fwww.wwtns.on…> - on twitter: wwtns@TheoreticalWide You are cordially invited to the lecture Arthur Leblois CNRS, IMN Bordeaux, France on the topic of *Circuit Mechanisms of Sensorimotor Learning in the Cortico-Basal Ganglia-Thalamocortical Network* The lecture will be held on Zoom on October 28, 2026 at *11:00 am ET * > To receive the link: https://www.wwtns.online/register-page > *Please pay attention to the time change!* Europe has switched to winter > time whereas the United States will switch on November 1. > > As a result, the seminar will begin at *11:00 a.m. EDT, which corresponds > to 4:00 p.m. CET*, rather than the usual 5:00 p.m. in Europe. > *Abstract: * The basal ganglia (BG) are essential for learning and adapting movements, yet their output is often unnecessary for executing well-learned actions. This paradox challenges existing models of BG function. I will present a biologically grounded model of the cortico-BG-thalamocortical loop, showing how this closed-loop network supports efficient motor adaptation and early movement acquisition. In our model, dopamine-driven plasticity, recurrent cortical dynamics, and feedback from the BG together shape motor output, even when BG output is not directly required for execution. This work provides a unified framework explaining how the BG-cortical circuit contributes to both learning and refinement of goal-directed actions. One important assumption of the model is that parallel feedback loops in the BG-cortical circuits form functional channels driving specific motor output, and I will show recent analysis of neuronal activity in the song-related circuit of zebra finch supporting this assumption.

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Discussion manuscript: validating pre-attack neural signals and their external EEG correlates
by נתי שטרן Oct. 25, 2026

Oct. 25, 2026

Dear computational neuroscience colleagues, I would welcome methodological feedback on a new discussion manuscript: A framework for validating neural signals before aggressive behavior in animal models relevant to autism and schizophrenia https://github.com/netanelcyber/psi-qeeg-bis/blob/6b79e9c39cd0532202659acbb… The central question is whether activity preceding an observed attack in an awake animal contains information that can be recovered from simultaneous external EEG and used to forecast future attacks beyond behavior, EMG and movement measurements. The proposal considers controls, ASD-relevant, SCZ-relevant and combined experimental conditions. It does not claim that animals have the corresponding human diagnoses; the combined condition requires its own construct validation. The analysis separates baseline differences, ongoing-action correlates and genuine pre-event prediction. Feedback would be particularly valuable on depth-to-surface signal mapping, latent-state models, causal preprocessing, animal-level holdout, calibrated warning probabilities, and false alarms per hour during continuous recording. Relevant existing synchronized depth/EEG/video datasets would also be helpful. This AI-assisted manuscript is a hypothesis and proposed validation framework. It contains no new experimental data, trained predictor or validation results, and has not been peer reviewed or accepted by a preprint server. AI assistance and pending author disclosure fields are stated in the draft. Please send comments privately to nsh531(a)gmail.com. Best regards, Netanel Stern Independent researcher, Israel

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Postdoctoral Position in Computational/Theoretical Neuroscience at UC San Diego
by Marcus Benna Oct. 23, 2026

Oct. 23, 2026

A postdoctoral position in computational neuroscience with flexible start date is available in the lab of Dr. Marcus Benna <https://biology.ucsd.edu/research/faculty/mbenna> at the University of California, San Diego. Our research seeks to understand how neural information processing under noisy and resource-constrained conditions allows the brain to efficiently perform computational tasks and control relevant behaviors. This position <https://biology.ucsd.edu/jobs/postdoc#postdoctoral-position-computationalth…> will involve the analysis of neural activity data (calcium imaging or electrophysiology) collected by our collaborators, as well as theoretical modeling of learning and task performance in neural networks. Our research group <https://bennalab.biosci.ucsd.edu/> is part of the vibrant Department of Neurobiology at UCSD, which is highly collegial, and offers many opportunities for collaborations, both formal and informal. Postdoctoral trainees are encouraged to attend seminars and present their work at departmental events. Our group is located in Tata Hall and shares space with several experimental neuroscience laboratories. We offer a stimulating environment with opportunities to develop new research directions and supportive mentorship for individual career development. The applicant should hold a PhD in computational neuroscience, physics, applied math, computer science, data science, or a related field, preferably with a degree date no more than two years before the start date. Candidates should have a strong quantitative background and programming skills. Experience in computational modeling, machine learning and/or data analysis is necessary for this position. Strong verbal and written communication skills are required. We’re looking for collaborative, motivated individuals who can conduct an independent research project and work as part of a team. To apply, please email Dr. Marcus Benna (mbenna(a)ucsd.edu) with the subject line “Postdoc Application”, and include - A cover letter/research statement that summarizes your experience, contributions to science, as well as research interests and how they align with the lab’s work. - CV with publication list - Names and contact information of 3 references Review of applications will begin on Nov. 13th. Best, Marcus ========================== Marcus K. Benna Assistant Professor Department of Neurobiology School of Biological Sciences University of California, San Diego

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Postdoc position in retina computational modeling applied to psychiatry at LORIA, Nancy, France
by Laure Buhry Oct. 22, 2026

Oct. 22, 2026

A postdoctoral position is available at LORIA (Laboratoire Lorrain de Recherche en Informatique et ses Applications), Nancy, France, in the Neurorhythms (https://neurorhythms.loria.fr/) team on the MERGES ( https://piq.inria.fr/projets/#merges https://piq.inria.fr/en/projets/#merges) project funded by the Inria Quadrant Programme. The work will be conducted in collaboration with experimentalists at Christophe Ribelayga's lab, University of Houston, TX, and clinicians at Steven Silverstein's lab, University of Rochester, NY. The aim of this project is to test pathophysiological hypotheses in schizophrenia spectrum disorders and to identify novel therapeutic targets through physiologically realistic modelling of retinal signalling, used as a peripheral window into brain function. The postdoctoral fellow will contribute to computational modeling of retinal circuits and to hypothesis-driven analyses, including short research stays at our collaborating laboratory in the United States. *Start date* : as soon as possible. *Contract duration* : 2 years, with possible renewal of 1 year contingent on successful annual review of the programme. *Monthly gross salary* : 2948 € (French salary scale) *Qualifications:* Prior experience with computational neuroscience is required, in particular with conductance-based models. Prior knowledge and practice in scientific computing, signal analysis or applied mathematics is preferred. A strong interest in retinal functioning and applications in Psychiatry is mandatory. *Application:* Prospective postdocs can contact laure.buhry(a)loria.fr for more detailed information, or directly send a CV and short statement of interest for application. -- Laure Buhry https://members.loria.fr/LBuhry/

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Fully-funded Research Assistant position in Neuroimaging studies at University of South Carolina
by Z S Oct. 22, 2026

Oct. 22, 2026

Dear all, Description: Dr. Sha’s lab (https://shazhiqiang.wixsite.com/sha-lab) at the University of South Carolina is seeking *a fully-funded Research Assistant*. Our lab is affiliated with the Carolina Autism & Neurodevelopment Center, the Institute for Mind & Brain, and working closely with the McCausland Center for Brain Imaging in Columbia, the center of SC Metropolitan Statistical Area. Our lab explores the mechanisms of atypical brain development and neurodevelopmental disorders (e.g., autism spectrum disorders) by leveraging computation modeling to bridge neural circuitry, exposure (e.g., early life adversity) and psychopathological phenotypes, and treatment outcomes. These innovative projects will leverage state-of-the-art computational models, supported by the Brain Imaging Center (with 3T and high-field 7T MRI scanners) and the Biobehavioral Research Center. This position provides an excellent opportunity for a self-motivated student to gain hands-on experience with neuroimaging (e.g., MRI) and computational modeling, making it ideal preparation for a future graduate or medical career. Research Assistant will be actively involved in the scientific process and are encouraged to contribute meaningfully to publications. We fully support research assistants in leading first-author publications and presenting their work at international conferences. Duties: · Computational modeling; statistical modeling · MRI data collection, processing, analysis; present results and publish papers · Manage daily administrative operations of the lab (e.g., scheduling and communication) Requirements: · Bachelor’s degree in a relevant science (e.g., neuroscience, math, biostatistics, biomedical engineering and etc.) · Experience with clinical and MRI data collection and data analysis. · Candidates with coding experience are preferred. How to apply: Please submit your CV to Dr. Sha (zsha(a)mailbox.sc.edu)

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Fully funded lab manager position on social neuroscience lab
by Speer, Sebastian Oct. 21, 2026

Oct. 21, 2026

We’re hiring a full-time lab manager/research assistant to join the Coupled Minds Lab at Texas A&M University! Our lab, led by PI Sebastian Speer, studies how conversations shape the way people connect, change their minds, and learn. We combine fMRI hyperscanning, natural language processing, and computational modeling to investigate how people explore ideas together and build consensus in interactions with human and AI partners. The lab manager will help lead data collection for fMRI hyperscanning studies, analyze naturalistic fMRI data and conversation transcripts, and apply computational methods to study social interaction. This position offers hands-on research experience for someone considering a PhD in psychology or neuroscience. Qualifications: A bachelor’s degree in psychology, neuroscience, computer science, or a related field is required. Prior research experience is preferred. Salary: $45,000 per yearLocation: College Station, TexasStart date: As soon as possible Applications will be reviewed on a rolling basis until the position is filled. Apply here: https://tamus.wd1.myworkdayjobs.com/TAMU_External/job/College-Station-TX/Re… Learn more about the lab: https://coupled-minds.github.io/ --- Sebastian Speer Assistant Professor Psychological & Brain Sciences Texas A&M University

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