57 parallel-processing-bioinformatics PhD positions at Delft University of Technology (TU Delft)
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are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words
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Corrosion Technology? Join us on our journey to ensure Safe Operation of Military Systems. Job description Join the Corrosion Technology and Electrochemistry (CTE) group, part of the Department of Materials
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
@tudelft.nl . For more information about the application procedure, please send an e-mail to recruitment-tbm@tudelft.nl . After an initial selection, a first round of online interviews will be planned in
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28 Oct 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Computer engineering Engineering » Control engineering Researcher Profile
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to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and
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asymptotic analysis of stochastic processes Impact: Faster detection of anomalies and reliable uncertainty quantification Job Description As a PhD candidate in Mathematical Statistics, you will develop novel
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procedure, please send an e-mail to recruitment-tbm@tudelft.nl . After an initial selection, a first round of online interviews will be planned in the first week after the deadline. Application procedure
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contact L.C.Rietveld@tudelft.nl Application procedure Are you interested in this vacancy? Please apply no later than 7 November 2025 via the application button and upload the following documents: CV
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Description Are you passionate about generative artificial intelligence and ships? Join us in innovating the ship design process as we know it. Job description Introduction Generative AI is transforming how
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cellular processes at once rather than relying on a few individual proteins. This raises a fundamental question: how do complex cellular networks collectively ensure evolutionary robustness? Within the ERC