Dear colleagues, We have several openings for Postdoctoral Researchers to work at the intersection of Machine Learning and Computational Neuroscience funded by the ERC Consolidator Grant “DeepCoMechTome: Using deep learning to understand computations in neural circuits with Connectome-constrained Mechanistic Models“. The goal of DeepCoMechTome is to develop simulation-based machine learning tools that will make it possible to build neural network models that are both biologically realistic and computationally powerful. Some relevant prior work can be found in https://www.biorxiv.org/content/10.1101/2023.03.11.532232v1. We are looking for candidates with a strong quantitative background and PhD in a relevant discipline, ideally in computational neuroscience, machine learning or numerical simulation, a genuine interest in collaborative work at the interface of machine learning and neuroscience, and strong programming skills (ideally Python and relevant deep learning frameworks). Our research group (https://www.mackelab.org <https://www.mackelab.org/>) develops methods in machine learning and artificial intelligence to accelerate scientific discovery, with a particular focus on neuroscience. We aim to provide an interdisciplinary, collaborative and supportive work environment which emphasizes diversity and inclusion. We are embedded in Tübingen’s internationally renowned research community in artificial intelligence and computational neuroscience, including the Cyber Valley Initiative, the Tübingen AI Center, the ELLIS initiative, the Excellence Cluster Machine Learning, the Bernstein Center for Computational Neuroscience, the Hertie Institute for AI in Brain Health and dedicated MSc Programs in Machine Learning and Computational Neuroscience. We are situated in the AI Research Building, in close proximity to the Max Planck Institutes for Intelligent Systems and Biological Cybernetics, and participate in the two International Max Planck Research Schools (IMPRS) `Intelligent Systems’ and`Mechanisms of Mental Function and Dysfunction’. The University of Tübingen is committed to equal opportunity, diversity and inclusion. In case of equal qualification and experience, physically challenged applicants are given preference. The University of Tübingen aims at increasing the share of women in science and highly encourages female scientists to apply. We also explicitly encourage scientists from outside Germany to apply. Please submit your application materials to mls-jobs@inf.uni-tuebingen.de <mailto:mls-jobs@inf.uni-tuebingen.de>, including a CV with publication list, a statement of research interests (max. two pages), contact details of two referees, and a link to a code repository (or work samples). Application deadline is June 20, 2023. Candidates are encouraged to send their application material early, as we will start reviewing applications before the deadline. Initial fixed-term contracts will be for 3 years at level E13 TV-L with possible extensions, starting date is flexible. Part-time positions are possible. Hiring is carried out by the Central Administration. For further details and instructions, see www.mackelab.org/jobs <http://www.mackelab.org/jobs>. Best, Jakob Macke Prof. Dr. Jakob Macke Machine Learning in Science; Cluster of Excellence "Machine Learning”, University of Tübingen Adjunct Senior Research Scientist, Department of Empirical Inference; Max Planck Institute for Intelligent Systems Tübingen Director, Bernstein Center for Computational Neuroscience www.mackelab.org <http://www.mackelab.org/>