Postdoctoral Researcher in Systems Neuroscience, Visual Behavior, and Machine Learning (NeuroAI) University of Bonn in Germany

The University of Bonn Medical Center, in collaboration with the University of Göttingen, is offering a fully funded postdoctoral position in systems neuroscience, visual behavior, and machine learning (NeuroAI). This joint European Research Council (ERC)-funded project is led by Professors Tobias Rose (University of Bonn) and Fabian Sinz (University of Göttingen), and is situated at the interface of experimental and computational neuroscience.

The successful candidate will be based in the RoseLab at the University of Bonn and will lead the experimental side of the project, working closely with the SinzLab in Göttingen, which focuses on theoretical and computational modeling. The research aims to investigate neural representations during naturalistic vision in action, using cutting-edge techniques such as miniature two-photon imaging, gaze reconstruction in freely moving mice, and deep network models of dynamic vision. The project offers a unique opportunity to combine experimental neuroscience with advanced machine learning approaches, providing strong visibility at the neuroscience–AI interface.

Key research areas include systems neuroscience, visual behavior, deep network models, neural data analysis, mouse behavior, and computational neuroscience. The position involves designing and running experiments in mice, performing neural recordings (with a focus on two-photon imaging), developing behavioral tracking and gaze reconstruction pipelines, analyzing large-scale neural and behavioral datasets, and developing or applying deep network models and encoding/representation models. The postdoc will also present results at meetings and contribute to publications.

Applicants should have a PhD in neuroscience, computer science, physics, engineering, or a related field, with experience in in vivo imaging, rodent behavior, neural data analysis, computer vision, pose tracking, or machine learning/deep learning. Strong programming skills (Python preferred; MATLAB welcome) and excellent English communication skills are required. The position is highly collaborative, offering access to complementary expertise, close mentoring, and a highly interactive research environment. There are strong opportunities for method development, collaboration, and career growth.

The contract is for 4.5 years, with a start date of April 1, 2026. The position is fully funded by an ERC grant, though specific salary details are not provided. To apply, candidates should send a single PDF including a cover letter (1–2 pages), CV, publication list, and contact details for 2–3 referees to [email protected], cc: [email protected]. For more information, visit the project and lab websites linked in the announcement.