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qualified and motivated postdoctoral researcher. The group studies the behavioral, neural, and computational principles behind human learning and decision-making in social environments. Our interdisciplinary
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description The postdoctoral project is focused on development and the exploitation of machine learning tools to accelerate the analysis of microtomography data at the MAXIV synchrotron facility. MAXIV
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PhD students in the Automation group, with the primary goal of qualifying for a future academic career. Contribute to research projects within discrete-event systems, supervisory control theory, and
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group. Main responsibilities Conduct research in collaboration with senior researchers and PhD students in the Automation group, with the primary goal of qualifying for a future academic career
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constrained environments - Data-driven and learning based control - Meta-learning for emergent behavior in multi-agent systems - Learning-based cognitive awareness, contextual and neuro-symbolic reasoning
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motion planning - Predictive collaboration with heterogeneous teaming - Multi-agent navigation in constrained environments - Data-driven and learning based control - Meta-learning for emergent behavior in
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. This unique position combines advanced finite element modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an
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simulations to experiments in subatomic physics. The Plasma Theory group within the Division conducts research on acceleration and radiation generation in magnetic fusion, laser-produced and astrophysical
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modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an innovative startup partner. You will be
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining