52 phd-studenship-in-computer-vision-and-machine-learning PhD positions at Ghent University
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-of-the-art in machine learning, (probabilistic) modelling, system identification and numerical optimization. How to apply Send your CV, containing one or more references, a copy of your diploma (if already in
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your knowledge and skills on state-of-the-art in machine learning, (probabilistic) modelling, system identification and numerical optimization. How to apply Send your CV containing one or more references
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techniques) at UGent combined with machine learning, deep learning and data fusion modelling to enable development of novel decision support systems for variable rate fertilization and manure application. He
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excellent predisposition to learn how to work with these data is a basic requirement). What we can offer you: The PhD appointment is full-time for 4 years (contingent on a positive evaluation after the first
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, sensing and optimization of the electromechanical aspects of industrial machines, with an emphasis on Industry 4.0 technologies such as machine vision, AI or digital twins. A digital twin can be defined as
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at national and international conferences. You may be asked to teach exercise sessions (in English) for a course taught by the department staff, or to help in the supervision of master’s theses. Your ultimate
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electric machine manufacturing or repair. The initial contract duration will be one year, in which you are hired as a PhD researcher. The contract can be extended to 4 years in total, under the condition
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part of a pioneering study that explores these developments. We are seeking a highly motivated PhD researcher for an innovative 4-year interdisciplinary research project examining the trajectory
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biodiversity responses to future climate and canopy change. YOUR JOB Here we advertise for one PhD position which will be part of the broader CanopyChange project and team. This particular PhD position will
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”, we offer a fully-funded PhD position. About DIADAPT: Diatoms are a group of highly diverse, globally dominant microalgae which contribute significantly to global carbon fixation and biogeochemical