92 component-labeling-agorithm-cuda PhD positions at University of Groningen in Netherlands
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, which is part of the Faculty of Science and Engineering (FSE) at the University of Groningen. The University of Groningen, established in 1614, is one of the oldest and largest research universities in
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). An assessment may be part of the procedure, consisting of psychological tests and an interview. The University of Groningen strives to be a university in which students and staff are respected and feel at home
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in collaboration with diverse partners and stakeholders, contributing not only to academic output but also to visible societal change. The PhD project is part of the “Wad Gaat Om” program, which aims
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only to academic output but also to visible societal change. The PhD project is part of the “Wad Gaat Om” program, which aims to sustainably reduce plastic waste and usage in the Wadden Sea area through
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PhD thesis within the next three years is to be expected. A PhD training programme is part of the agreement and the successful candidate will be enrolled in the Graduate School of Science and
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(University of Granada), dr. Lotte van Poppel (University of Groningen) and dr. Janina Wildfeuer (University of Groningen). The position is part of the project The Normativity of Multimodal Arguments, which is
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). The position is part of the project The Normativity of Multimodal Arguments, which is funded by the Dutch Science Foundation (NWO). In this project, we combine description- and explanation-oriented insights
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). The position is part of the project The Normativity of Multimodal Arguments, which is funded by the Dutch Science Foundation (NWO). The project aims to integrate description- and explanation-oriented insights
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of Groningen and will tackle a project on making the directed evolution of biocatalysts predictable by machine learning. As part of the ML-GUIDE team, you will closely collaborate with researchers to identify
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mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant