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on the modelling and optimisation of PRO systems using advanced Computational Fluid Dynamics (CFD) and Machine Learning (ML) techniques. This role offers an exciting opportunity to contribute to cutting-edge
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the project. Qualified candidates should have: A PhD degree in Computer Science, Electrical Engineering or equivalent. Research interests and a scientific track record in Edge Computing research fields, such as
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relation to food technology, food chemistry, and food nutrition in a broad sense. Teaching activities will include supervision of student projects at different levels (BSc, MSc, PhD). You will engage in
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activities in relation to food technology, food chemistry, and food nutrition in a broad sense. Teaching activities will include supervision of student projects at different levels (BSc, MSc, PhD). You will
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use your skills to answer fundamental biological questions in health and disease. The successful candidate is expected to leverage their skills in proteomics and computational analysis to interrogate
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recruitment and supervision of future PhD students and postdocs. We seek applicants who: Hold a PhD in molecular biology, biotechnology, bioengineering, or related fields. Demonstrate enthusiasm for complex
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. The applicant should have: A PhD in meteorology, climatology or other related fields Experience in mesoscale modelling, preferably WRF Experience of scientific programming and running code on HPC systems
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position: This position is part of ‘SEEDFOOD: Functional and Palatable Plant Seed Storage Proteins for Sustainable Foods’, a Challenge Program project funded by the Novo Nordisk Foundation. SEEDFOOD is a
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. The position is part of DTU’s Tenure Track program. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial
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DTU’s Tenure Track program. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic