52 parallel-computing-numerical-methods Postdoctoral positions at Technical University of Munich in Germany
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10.08.2021, Wissenschaftliches Personal Positions in the Formal Methods for Software Reliability group of TU Munich led by Prof. Jan Kretinsky: - postdoc in the area of quantitative verification
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems
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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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] Subject Area: Representation Theory Appl Deadline: 2025/07/31 11:59PM (posted 2025/07/01) Position Description: Position Description The TUM School of Computation, Information and Technology at the Technical
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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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and satellite-based remote sensing data using High-Performance Computing at LRZ Publication of the results in scientific journals Assistance in teaching REQUIREMENTS: An above-average degree in
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(ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University of Munich (TUM), together
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mobility systems through practical and laboratory tests as well as sophisticated simulations. We not only publish research results gained at numerous conferences and in journals, but also make our software
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of Computation, Information and Technology (CIT), located on the Garching Campus, starting October 01, 2025 or later. The group is seeking a highly qualified candidate for a postdoctoral position who possesses
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
control of such systems, taking particularly into account model uncertainties as well as limitations pertaining to acquisition of data, communication, and computation. We apply our methods mainly to human