37 software-defined-networking-"IMEC" Postdoctoral positions at Technical University of Munich in Germany
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, and opportunities for developing a strong academic network. We support Open Science and Open Access publications. The salary is based on your qualifications and personal suitability in accordance with
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provide quality assurance for research and software development tasks Define the overall architecture of the VIOLET research prototype, focusing on its role as a methodological demonstrator and ensuring
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
of future communication networks”. TU Dresden and the Technical University of Munich have joined forces to form the 6G-life research hub in order to drive cutting-edge research for future 6G communication
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, clustering, neural networks) for spectral interpretation, segmentation, and material identification. • Create and curate a dedicated HSI spectral library for cultural heritage materials, linking reference
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quantum networks” (TV-L E13) (f/m/x) for the project "6G and Quantum Technology (6GQT)", which is being funded by the Bavarian State Ministry of Economic Affairs, Regional Development and Energy. ). The
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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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explore new topics while playing nice in a team. Your main task will be the development, conceptualization, and eventual implementation of new design automation methods and software for your field, e.g
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a unique opportunity to contribute to cutting-edge research on remote robotic control under network uncertainties, focusing on the development of fault-tolerant and adaptive control architectures
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Safety, Reliability and Resilience of AI-based Robotics. The successful candidate will have the opportunity to engage with the RIG network, collaborate with academic and industrial partners, and contribute
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often represented in large neural networks that are hard to analyze and whose decision processes cannot be interpreted by humans. To make this technology available without sacrificing safety concerns, we