44 bio-inspired-computing Postdoctoral positions at Technical University of Munich in Germany
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to contribute to groundbreaking work in our research area. About the Program: We are implementing a program that creates an additional two year postdoctoral position exclusively for female researchers working in
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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
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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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good publication track record Above-average master’s degree in computer science, electrical/ mechanical engineering, applied mathematics, or a similar engineering-oriented quantitative discipline
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14.12.2022, Wissenschaftliches Personal The BMBF-funded position is part of the CoMPS project, which is a multidisciplinary project combining the fields of mathematics, computer science, geophysics
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30.05.2023, Wissenschaftliches Personal Bioinformatician/Computational Biologist/Systems Immunologist (f/div/m) for two years initially with a possibility of extension to 5 and more years
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22.03.2021, Wissenschaftliches Personal The 3D AI Lab at the Technical University of Munich is looking for highly motivated PhD students and PostDocs at the intersection of computer vision, machine
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22.11.2020, Wissenschaftliches Personal The 3D AI Lab at the Technical University of Munich is looking for highly motivated PhD students and PostDocs at the intersection of computer vision, machine
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15.06.2020, Wissenschaftliches Personal The 3D Understanding Group at the Technical University of Munich is looking for highly motivated PhD students and PostDocs at the intersection of computer
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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