245 data-science-"https:"-"https:"-"https:"-"https:"-"Computer-Vision-Center" PhD positions in Netherlands
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- Delft University of Technology (TU Delft)
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the country of the host organization for more than 12 months in the 36 months immediately before the call deadline or recruitment date Information and application Are you interested in this position? Please
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collaborators, and engage with the broader research community at the Bijvoet Centre and the Faculty of Science. Visit the Kaiser Lab and the Bijvoet Centre websites for more information. Your qualities You are
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of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection
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Integrated optics is currently experiencing unprecedented growth, driven largely by the rapid expansion of artificial intelligence (AI), cloud computing, and high-performance data processing
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students and 4200 academic staff (44% international). The Faculty of Science and Engineering unites researchers across biology, neuroscience, engineering and data science. The project will be embedded within
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, sharing knowledge and expertise to develop innovative solutions with meaningful societal impact. Please see our work for more information: Offshore and Dredging Engineering . Job requirements You are highly
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of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection
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carbon properties influence PFAS removal in drinking water treatment. You will combine laboratory experiments, column studies, and data analysis to identify the factors governing PFAS breakthrough
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, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at
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. To address this challenge, the project aims to develop structural health monitoring technologies based on a digital twin. The digital twin will combine information from the physical structure with models and