21 parallel-computing-"INSERM" Postdoctoral scholarships at Technical University of Munich
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18.09.2024, Wissenschaftliches Personal We have several 𝐏𝐡𝐃 & 𝐏𝐨𝐬𝐭𝐃𝐨𝐜 𝐨𝐩𝐞𝐧𝐢𝐧𝐠𝐬 in our Visual Computing & AI Lab in Munich! Topics have a strong focus on GenAI, including 3DGs
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of targeted therapies. Analyzing high-dimensional single-cell data has its own statistical and computational challenges, and standard tools often cannot be applied. The purpose of the position and goal
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22.10.2020, Wissenschaftliches Personal PhD and PostDoc Positions in Visual Computing & Artificial Intelligence: we are looking for highly-motivated PhD students and PostDocs at the intersection
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., for quantum computing, microfluidics, or conventional circuits and systems. Our focus on interdisciplinary partnerships and networks will enable you to meet many interesting people (at places all over the world
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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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Engineering, Computer Engineering, Computer Science, or a closely related field Strong background in robotics fundamentals: kinematics, dynamics, control, planning Proficiency in programming (C++, Python), and
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The TUM School of Computation, Information and Technology at the Technical University of Munich (TUM) welcomes applications for a PhD or Postdoc Position (m/f/d, 100%, 2 years+) in Numerical Mathematics
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technologies to fundamental physics questions. The advertised positions will be part of the project “QS-Gauge: quantum simulation of lattice gauge theories”, funded by the Emmy Noether programme of the DFG
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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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that algorithmic parameters are tuned so that the over-approximation of the computed reachable set is small enough to verify a given specification. We will demonstrate our approach not only on ARCH benchmarks, but