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will have the chance to use cutting-edge techniques, including super-resolution microscopy (PALM, Smdm), single-particle tracking, machine learning, and latest state-of-the-art biochemical analysis tools
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neuroimaging (fMRI, MEG, iEEG) and behavioral data. This PhD position is part of the Natural Auditory Scenes in Humans and Machines (NASCE) project, funded by the ERC Synergy Grant, and hosted at Maastricht
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optimizations and approaches inspired by machine learning within the framework of cognitive radar; and C) verify the developed approaches with suitable simulations and experimental demonstrations. Specifically
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and a scientific programmer. You will be supervised by both Rianne de Heide and Jelle Goeman. One PhD student will be appointed at the UT, and one PhD student at the LUMC. We collaborate very closely
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particular, Intelligent Data Engineering (INDElab) group, and their activities; assist in educational activities and supervision of bachelor and master students; complete and defend a PhD thesis within the
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our research team in cryptography. The ideal candidate will have a strong background in mathematics, computer sciences, engineering, or a closely related field. The candidate must be highly motivated
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economicssystems/ operations management, econometrics, machine learning, extensive data analytics and qualitative research methods. The student will collaborate closely with advisors to identify, develop, and carry
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of biased decision-making in machine learning (ML)? This PhD position offers a unique opportunity to contribute to cutting-edge research in algorithmic fairness, ensuring that automated decision-making
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-heuristic search algorithms such as Quantum Annealing (QA). Your contributions will be pivotal in advancing the field of DSE in the computer system domain. This PhD position offers the chance to not only push
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that can be used for training machine learning and deep learning models. You will work in tight collaboration with other researchers in Nijmegen, Delft and at the Hubrecht Institute (van Oudenaarden group