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systems Reinforcement Learning and Agentic Control: Hands-on experience with reinforcement learning, multi-agent systems, or planning-based agents for autonomous vehicles or robots operating in dynamic
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/admittance, force control Experience with Artificial Intelligence and deep learning concepts for robotics computer vision, tactile sensing, reinforcement learning Experience with robotic simulation tools e.g
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cohort studies with a primary focus on cancer, immunological diseases, and neurodegenerative disorders. Key Accountabilities Data management: overview, pre-process, QC, and maintenance of integrated
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procedures Innovative teaching experience and interest to develop these further Fluency in English is required; good command of French, Luxembourgish and / or German is considered an asset We offer
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control) using real operator-grade datasets (traffic indicators, network KPI's, configuration logs and energy measurements when available). • Investigating and combining multiple energy-saving levers (e.g
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multilingual university. Therefore, the command of at least two of the University languages is necessary: French, English, German We offer Multilingual and international character. Modern institution with a
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control, documentation, automation) Soft skills Ability to work effectively in interdisciplinary teams spanning computational and experimental research Strong analytical and problem-solving skills, with
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of Systems Biology and Biomedicine - in the lab, in the clinic and in silico. We focus on neurodegenerative processes and are especially interested in Alzheimer's and Parkinson's disease and their contributing
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evaluating adaptive Medium Access Control (MAC) and network‑layer protocols to enhance performance in shared spectrum environments. Developing AI‑driven methods for real‑time interference prediction and