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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following
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sluice, which will then be used in a learning framework to design an automatic controller to optimize the usage of the sluice under various conditions. The other project will address challenges related
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-products. Monitor and control the migration of radionuclides and heavy metals throughout industrial processes. Optimization of Industrial Processes: Utilize nuclear techniques to enhance the efficiency and
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closed-loop optimization. Benchmark AI-assisted methods against classical control approaches and assess scalability and robustness under realistic noise conditions. 2. Neural Ansätze for Quantum
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then be used in a learning framework to design an automatic controller to optimize the usage of the sluice under various conditions. The other project will address challenges related to Sustainable Water
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an optoelectronic process for 980 nm high-power diamond laser diodes. In this context, the role of the LSPM is to provide polycrystalline diamond layers 2 to 4 inches in diameter with optimized mechanical
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University Abu Dhabi invites applicants to apply for the open Post-doctoral Associate position to perform primarily research on Reinforcement Learning, and/or Optimal Control, and/or Model Predictive Control
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Postdoc Appointment Term: 2026-2028 Appointment Start Date: Early 2026 Group or Departmental Website: https://med.stanford.edu/bronte-stewart-lab.html (link is external) How to Submit Application Materials
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mathematics to work with Axel Ringh on a project funded by the Swedish Research Council (VR). The project is centered around inverse optimal control/inverse reinforcement learning, both for continuous-time and
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. Working closely with partners in the IMPRESS project, you will analyse their materials and provide valuable insights to help optimize device performance. Additionally, you will support collaborators by