Are you excited about using machine learning to quantify the computational complexity of biological neurons, or about designing neuron-inspired expressive units networks that improve the performance of reinforcement learning robots? Join us as a
Postdoctoral Researcher
in computational neuroscience and machine learning
for our Neuro-AI project (m/w/d; E13 TV-L, 100%).
University of Tübingen, Department of Computer Science
We seek highly qualified researchers to advance neuro-inspired machine learning for recurrent neural networks and reinforcement learning to start at the earliest possible date. The overarching goal of the project is to design more capable and efficient AI systems using neuroscience-inspired computational building blocks.
Our recent work has shown that a single expressive leaky-memory (ELM) neuron (Spieler et al., 2024) can solve tasks requiring extremely long memory. The next major steps are (i) scaling from single expressive units to structured networks of such neurons, and (ii) characterizing the computational components and complexities of diverse neuron types. These insights will help us both to better understand the brain and to identify powerful architectural primitives for advanced AI models. We will explore how ELM-based networks can advance AI in challenging domains, including language modeling and representation learning for robotic agents.
The project is jointly supervised by Anna Levina, a computational neuroscientist, and Georg Martius, a machine learning and robotics researcher.
Your profile
Applicants should hold a PhD in computer science, neuroscience, physics, mathematics, or a related field. Expertise in machine learning (especially RNNs), computational modeling, or theoretical neuroscience is advantageous. The position is fixed-term (2.5 years), with a salary according to the German public sector (100%, E13 TV-L).
Research environment
Tübingen is a leading international hub for machine learning and computational neuroscience. You will work in a lively, collaborative environment with close ties to the Cluster of Excellence “Machine Learning: New Perspectives for Science” at the University of Tübingen (www.ml-in-science.uni-tuebingen.de) and Hertie Institute for AI in Brain Health (https://hertie.ai). Also on our campus are the Tübingen AI Center, the Max Planck Institute for Intelligent Systems, and the Ellis Institute.
Please fill out the following form (https://forms.gle/96yVbWCUvG6qnCPV8) and upload the usual documents (cover letter, curriculum vitae, copies of certificates, list of publications, 2-3 names of referees) together with a 1 page summarizing your research achievements by January 12, 2026. If you have nay questions, reach out to Anna Levina or Georg Martius.
The University aims to increase the proportion of women in research and therefore urges suitably qualified women scientists to apply. Qualified international researchers are expressly invited to apply. Disabled persons with equal aptitude will be given preferential consideration. Staffing will be conducted by the central administration of the University of Tübingen.