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talented individuals passionate about AI, Human-Computer Interaction, Eye-Tracking, and their responsible applications. Ideal candidates will have: • An M.Sc. degree (or equivalent) in Computer Science, Game
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-performance computing infrastructure. Opportunities to publish in high-impact journals and present at international conferences. Career development support and mentoring. Collectively agreed remuneration
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coordinating reactions to occur at the right time and in the right place, and one remarkable way that cells organize biomolecules to perform reactions is by utilizing the physics of binodal coexistence, called
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-Scripting very good knowledge in programming, preferably in Python,Fortran, Matlab or R experience in the environment of High Performance Computing (HPC) is desirable, but not mandatory capability to work in
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methods (LBM). For fluid simulations, we utilize the high-performance LBM framework waLBerla, predominantly written in C++, but increasingly adapted for GPU computations through automatic code generation
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to perform theoretical physics research at the interface of quantum information, condensed matter and high-energy physics. A strong background and interest in one or more of the following topics is desirable
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modeling and prediction Integration of perception, planning, and control for robust real-time robotic performance Requirements PhD Position: Master’s degree in Robotics, Mechanical Engineering, Electrical
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or Postdoc Position in Numerical Mathematics m/f/d, 100%, 2 years+ As part of the second phase of the DFG funded Priority Programme SPP2311, the Chair for Numerical Mathematics under the leadership
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, computer scientists and physicists to combine our extensive expertise in neuroscience, imaging and AI into viable solutions Publish your results in high-quality scientific articles National and international
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, alternative discretization methods (e.g., Lattice Boltzmann Methods), and high-performance computing. A selection of possible research areas can be found on our website: https://www.math.cit.tum.de/math