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Field
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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adaptive, automated decision-making tools (e.g., traffic signal control, human–vehicle coordination, logistics optimization, route planning) using reinforcement learning in dynamic environments. Explanation
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offer: • A dynamic and interdisciplinary team with a strong focus on translational cancer re-search, tumor-immunity and genomics and close cooperation with clinicians • Excellent core facilities to
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young, dynamic, and interdisciplinary research team Access to state-of-the-art imaging technologies and preclinical research facilities A wide range of training, mentoring, and career development
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on an attractive research campus at the TZA Aachen ( https://tza-aachen.de ) and the Forschungszentrum Jülich The opportunity to gain your reputation in a dynamic and highly active research field Further
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and the Leibniz association Training and scientific development opportunities in an international environment and an excellent working atmosphere in a very dynamic and professional team Extensive state
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(TV-L Brandenburg). Background: Addressing climate change and biodiversity loss requires a deep understanding of global land-use dynamics and the economic trade-offs involved. We aim to develop and
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cellulose and yield fundamental insights into supramolecular structure and dynamics in biomaterials. Your profile We are looking for a candidate with the following qualifications: • Master’s degree in polymer
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mechanics (QM / MM) molecular dynamics simulations using a Quantum Centric Supercomputing (QSC) approach [1,2] for the QM problem. This will be integrated within the in-house MiMiC framework [3] and applied
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dynamic and professional team Extensive state-of-the-art equipment and infrastructure in various analytical methods The opportunity to present your data on international conferences and participate in