396 algorithm-development-"Prof"-"Washington-University-in-St"-"Prof"-"Prof" PhD positions in Netherlands
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the TU Delft to develop the next generation of synthetic CAAR cell therapy for serious autoimmune conditions. The project is a shared position between the CBI-department (Leiden University) and the
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Join our team at TU Delft to develop a novel electromagnetic flow meter for turbulent pipe flow
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. Wageningen University & Research offers plenty of opportunities for growth and development, with a strong internal recruitment policy and excellent training programmes. You will work on the greenest and most
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circular way can affect each other. While national strategies and missions give directions to address such grand societal challenges, local decisionmakers, such as municipalities and project developers, need
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scientists from the TU Delft to develop the next generation of synthetic CAAR cell therapy for serious autoimmune conditions. The project is a shared position between the CBI-department (Leiden University) and
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Join our team at TU Delft to develop a novel electromagnetic flow meter for turbulent pipe flow Job description Electromagnetic (EM) flow meters are widely used in industry for accurate measurements
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such cases, maps must be created or transformed from data rather than simply retrieved. The GeoTrAnsQData project addresses this by developing a GeoQA method that converts questions into executable geo
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expertise in quantum optics and information, and to develop mentorship skills by guiding MSc and BSc students. You will be part of a collaborative and supportive research environment at the heart of the Delft
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. The Pathology Department excels in clinical bioinformatics, focusing on diverse cancer types and the development of AI-driven diagnostic and prognostic tools. Both departments offer an inclusive, collaborative
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Intelligence (AI) and machine learning (ML) techniques. You will develop AI-based predictive models to anticipate user engagement, primarily using data collected through unobtrusive measurements (e.g., websites