60 phd-student-fpga PhD positions at Delft University of Technology (TU Delft) in Netherlands
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for personnel require alternative solutions, such as moving rolling stock maintenance to daytime on days or periods with less transport demand. The objective of this PhD project is to develop and demonstrate a
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learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts. For example, we would like to be able
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researchers from TU Delft and Meta Platforms as a PhD student in the newly established FUSE Lab! Job description As generative artificial intelligence is transforming the daily work of software engineers, TU
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researchers from TU Delft and Meta Platforms as a PhD student in the newly established FUSE Lab! Job description As generative artificial intelligence is transforming the daily work of software engineers, TU
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Description Want to rethink the future of software engineering at scale? Join researchers from TU Delft and Meta Platforms as a PhD student in the newly established FUSE Lab! Job description As generative
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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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Science and Engineering at the Faculty of Mechanical Engineering, in close collaboration with the Netherlands Defence Academy. The CTE group is a dynamic team of researchers, including PhD candidates
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social acceptance and fails to meet real needs. As part of the TACIT (Inclusive Technologies for Access and Social Participation) project, this PhD position will contribute to the co-design and co-creation
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Description Want to rethink the future of software engineering at scale? Join researchers from TU Delft and Meta Platforms as a PhD student in the newly established FUSE Lab! Job description As generative
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
to anticipate and manage. This PhD will develop a machine learning module to detect early warning signals of positive tipping points from techno-economic data, helping policymakers design adaptive strategies