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Postdoctoral Researcher – Ontology and Knowledge Graph Engineering, you will be contributing to the ongoing development of a general and interoperable modular architecture to build federations of simulation
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learning (RL), such as (but not limited to) Theory of online learning, reinforcement learning, and data-driven control Learning in games, and multi-agent RL RLHF and alignment in LLMs Representation learning
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models that significantly accelerate forging process simulations, optimize manufacturing parameters, and reduce dependency on computationally expensive simulations. This position offers the opportunity
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multiphysics simulation Develop multimodal decoupling algorithms Scalable O-skin fabrication and system integration onto robots and as wearables Realtime sensory mapping in complex environments Supervise master
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are we. We look forward to receiving your online application with the following documents: CV university transcripts a 2-3 page research statement two academic references copy of the PhD thesis and/or
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functional theory (DFT) outputs for representative quantum paraelectrics and use these force fields to perform lattice-dynamics simulations with explicit quantum mechanical treatment of the nuclei. Profile A
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online application including CV university transcripts a 2-3 page research statement two academic references copy of the PhD thesis and/or academic papers The expected starting date is spring 2025 or later
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(2) short description of your experience in using deep learning for image analysis Detailed CV (max. 3 pages) Publication list Copy of PhD diploma or equivalent Contact details of 2-3 references All