Postdoctoral Researcher (m,f,x) in Computational Neuroscience

In order to fill a fixed-term position in full-time (39.83 hours/week = 100%) at the earliest possible date, we are looking for a

Postdoctoral Researcher (m,f,x) in Computational Neuroscience

The Collaborative Research Center 1280 “Extinction Learning” (SFB 1280) is an interdisciplinary research consortium investigating the neural, cognitive, and behavioral mechanisms underlying extinction learning. Its 19 subprojects bring together researchers from neuroscience, psychology, medicine, and computational modeling across six research locations. The consortium is coordinated at Ruhr University Bochum (RUB). The Computational Neuroscience group at the Institute for Neural Computation at RUB investigates the neural and computational mechanisms underlying learning, episodic memory, and spatial navigation. Within SFB 1280, we use computational modeling to develop mechanistic accounts of learning and memory and work closely with experimental research groups to relate model dynamics to neural and behavioral data. Further information can be found at https://www.rub.de/cns

We are seeking a highly motivated postdoctoral researcher to investigate the neural mechanisms underlying episodic memory and spatial navigation. The successful candidate will develop quantitative spiking neural network models of the hippocampus in an interdisciplinary and collaborative research environment. The project aims to understand how hippocampal sequences during sharp-wave ripples (SWRs) are generated and how they are shaped by previous experience and neuromodulatory influences to support memory consolidation. Computational models will be developed in close interaction with experimental collaborators and validated against in vivo electrophysiological and behavioral data from rodents.

Scope: full-time

Duration: fixed-term, until 30.06.2029 (end of project)

Start: at the earliest possible date

Apply by: 2026-10-19

Your tasks:

• Develop and investigate quantitative spiking neural network models of hippocampal circuits involved in episodic memory and spatial navigation.
• Model how learning and previous experience shape hippocampal representations and sequence generation.
• Derive quantitative predictions from computational models that can be tested using experimental data.
• Analyze and integrate in vivo electrophysiological and behavioral data from rodents to constrain, test, and validate computational models.
• Work closely with experimental collaborators to establish an iterative exchange between computational modeling and empirical research.
• Present research findings at national and international conferences and workshops.
• Publish research results in international peer-reviewed journals.
• Contribute to the supervision and scientific mentoring of doctoral, master’s, and bachelor’s students where appropriate. (At the request of the applicant, participation in teaching is possible.)

Your profile:

• A successfully completed PhD in computational neuroscience, physics, computer science, cognitive science, or a closely related field
• A strong quantitative background and demonstrated experience in computational or mathematical modeling, preferably including biologically plausible or spiking neural network models
• Strong programming skills, preferably in Python, and experience with scientific computing and numerical simulations
• Ability to conduct research independently, develop new research questions, and take responsibility for the implementation and analysis of computational studies
• Excellent communication and teamwork skills and enthusiasm for close collaboration with experimental neuroscientists
• Excellent written and spoken English
• Experience with modern software development practices, version control, high-performance computing, and reproducible research workflows is an advantag

https://jobs.ruhr-uni-bochum.de/jobposting/1a216242df7d11a68fb762a850c9d76a08a289ea0?ref=AfA