78 postdoc-distributed-algorithms positions at Delft University of Technology (TU Delft)
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Description Are you excited about building cybersecurity platforms that are secure, explainable, and compliant by design? Do you want to combine real-time authorization, distributed ledgers, and verifiable
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, project managers, and postdocs with different nationalities. We share a drive to enable maritime operations of the future, harnessing our combined expertise to develop models and tools. Fostering an open
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Description Do you have significant experience with algorithms for interval path planning, and are you motivated to bring these closer to the railway industry? Then this position is for you! Job description The
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, postdocs, and faculty members. Our group focuses on understanding and mitigating corrosion processes, and on the development of electrocatalysts and electrochemical sensors through the synthesis of materials
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and PhD research topics, attracting funding to support PhD candidates and postdocs, and contributing to both the BSc Aerospace Engineering and MSc Control and Operations programmes. Collaboration is
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Engineering, Applied Physics, Applied Mathematics, Computer Science/Engineering, Geomatics, or a related field. You have knowledge of distributed, parallel, and high-performance computing suitable for handling
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based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored, and the findings of your project will be
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a multidisciplinary team of three researchers (two PhDs and one Postdoc), and in close collaboration with major industrial and research partners, including ESA (European Space Agency), Airbus, Rolls
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transportation systems may include a fleet autonomous cars, vans, and buses. This PhD position within FlexMobility will focus on the underlaying assignment and routing algorithms for real-time operation of
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expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model