88 model-driven-engineering PhD positions at Technical University of Denmark in Denmark
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interdisciplinary collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved through a strong academic environment of international top class
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collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved through a strong academic environment of international top class with
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Job Description The Department of Civil and Mechanical Engineering of the Technical University of Denmark (DTU) has an open PhD position on the topic of “Automated machine polishing of complex mould
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Job Description Are you driven by the idea of creating a more sustainable future through groundbreaking research? Do you want to work in a collaborative environment where your contributions can
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mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including
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to a two-year master's degree. You will work in a research team combining manufacturing engineering, solid mechanics, experimental methods and analytical/numerical modeling. A longer period at a
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more sustainable? If you share our passion for technology and the difference it can make in meeting the UN’s Sustainable Development Goals, perhaps you are one of our two new PhD students. At DTU Electro
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, including biosolutions. The institute’s tasks are carried out in interdisciplinary collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is
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. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved through a strong academic environment of international top class with correspondingly skilled
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to mechanical forces. We work with leading international groups on modeling and also conduct simulations at DTU. Our overarching goal is to understand and predict the mechanical behavior of metals during plastic