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. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process & microstructure with
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states of light, atoms, material objects, and their use for quantum sensing, quantum communication and quantum simulations are the core activities of the group. CBQS is a collaborative effort between the
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applications such as in-situ resource utilization (ISRU) or construction in reduced-gravity environments. Experience with simulation tools for thermal, mechanical, or flow processes (e.g., COMSOL, ANSYS
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qualifications. Possible topics are: The theory of ultrafast pump-probe experiments (e.g., time-resolved X-ray scattering and spectroscopy), simulations and data processing of actual ultrafast experiments, mapping
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and qualifications. Possible topics are: The theory of ultrafast pump-probe experiments (e.g., time-resolved X-ray scattering and spectroscopy), simulations and data processing of actual ultrafast
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models and reinforcement learning models for 3D graphs of materials to explore vast inorganic chemical spaces and design synthesizable energy materials. You will couple such models with physics simulation
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is expected to have a profound knowledge on most of the following topics: Robot control Deep Learning Medical imaging Preferably, the candidate has experience with: Robotic simulation tools Medical
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or quantitative modelchecking. -Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid, is aplus. -Familiarity with the basic concepts of quantumcomputing
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surgical robots across various surgical applications, using techniques such as advanced sensing, AI-based and reinforcement learning (RL)-based control, and soft continuum robot simulation. The starting date