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for physical systems. The postdoc will work on projects focusing on one or more of the following: Robot Learning & Autonomy – Developing algorithms that allow robots to learn (via exploration or imitation) from
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optical measurement setups, including the design and execution of channel sounding or propagation measurement campaigns Experience with RF/optical ray tracing simulation software, e.g., Wireless Insite
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models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental
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of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or experimental means. The PDA is expected to actively disseminate results through publications in
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, or related fields Strong background in game theory, mechanism design, control systems, and/or learning theory Programming proficiency and experience with simulation tools Excellent publication record in peer
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Engineering, Computer Science, Applied Mathematics, or related fields Strong background in control systems, machine learning, and scientific computing Programming proficiency and experience with simulation
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collaborators in material science. The developed technologies will be utilized to develop digital twin and soft robot-assisted simulations in the areas of brain machine interaction, wearable haptics, and
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Post-Doctoral Associate in the Center for Translational Medical Devices (Modeling) - Dr. Rafael Song
establishing collaborations across disciplines. Applicant must have a PhD in an engineering or biomedical-related field. Excellent skills relevant to the computational simulation of medical devices (3D solid
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Engine Simulator) is required. The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be
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the safety and robustness of human-robot interaction. The postdoc will work on projects focusing on one or more of the following: Learning-Based Control: Developing reinforcement learning, imitation learning