Postdoc position in Computational Neuroscience
Universität Bern · Bern, Bern, Switzerland
Skills in this posting
Extracted from the posting text by the instrument — the demand side, read literally.
The posting
**UniBE is interconnected.**
With us, you're part of an international community and benefit from interdisciplinary collaboration.
**Start Date**
01.10.2026 or by arrangement
**Employment Relationship**
fixed-term until 30.09.2027
**Institution / Workplace**
[Department of Physiology](https://physiologie.unibe.ch)
**Our Research**
A postdoc position is available at the University of Bern, Switzerland, at the [Department of Physiology](https://physiologie.unibe.ch/research/research_groups/computational_neuroscience/index_eng.html), under the supervision of [Prof. Walter Senn](https://physiologie.unibe.ch/about_us/team/people/prof_dr_phil_nat_senn_walter/index_eng.html). It starts with a 1-year contract, with the possibility of extensions.
At the intersection of neuroscience and artificial intelligence, this position offers the opportunity to generalize our recent [cortical model of multi-head self-attention](https://www.biorxiv.org/content/10.64898/2026.08.06.743205v1) (bioRxiv, 2026) toward in-context learning driven by biologically plausible neuronal error-circuits. Our model provides a mechanistic framework that unifies attention-based learning with gradient-based synaptic plasticity.
You will collaborate directly with the team behind [The Virtual Brain](https://ebrains.eu/data-tools-services/modelling-simulation/whole-brain-simulation) and apply these network models to study neurological disorders through the lens of disrupted sensory, motor, and cognitive self-attention.
Your work will further integrate with our ongoing research to extend the [Neuronal Least-Action Principle](https://elifesciences.org/reviewed-preprints/89674) into long-term temporal processing and spike-based learning paradigms.
Ultimately, you will be tackling a core challenge in the field: harnessing online learning in neuronal circuits to both decode human brain function and architect novel AI algorithms.
**Qualifications**
A PhD in computational neuroscience, machine learning, physics, applied mathematics, or a related quantitative field, with strong publication track record and mathematical skills.
**What we offer**
* Interdisciplinary \& international research environment at the frontier of neuroscience and AI, with genuine project ownership.
* Collaborations across artificial intelligence, experimental neuroscience and neuromorphic engineering beyond University of Bern.
* A beautiful working place in the UNESCO-listed capital of Switzerland, with walking distance to nature and mountains within reach, and an internationally competitive Swiss salary.
**Your Benefits**
Strong research infrastructure and international network
Team-oriented work
Inspiring work environment
Hands-on practical insights
**Working at the University of Bern**
The University of Bern not only offers exciting tasks but also an environment that actively promotes development, diversity, and equal opportunities. Discover what makes us stand out as an employer and how you can grow with us.
**Application and Contact**
Please send a single pdf document containing your CV, a statement of research interests, a publication list and contact details of two referees to walter.senn@unibe.ch and federico.benitez@unibe.ch. Informal enquiries are welcome. Applications are reviewed on arrival, latest by September 6, 2026; early applications encouraged.
**Questions about the position?**
Prof. Dr. phil. nat. Walter Senn
walter.senn@unibe.ch
**Questions about the application?**
Dr. Federico Benitez
federico.benitez@unibe.ch
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The PivotHop read
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