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activities, i.e., teaching and supervision of BSc and MSc student projects at DTU. We are looking for candidates with Strong skills in AI, Machine Learning, and/or Data Science, preferably with experience in
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background in Intelligence, Security, or a similar degree with an academic level equivalent to a two-year master's degree and with an interest (and ideally some experience) in Agent-based Modelling, Simulation
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motivated candidate with a background in chemical or process engineering and strong experimental and analytical skills. Join us to drive innovation in carbon capture and contribute to shaping Europe’s low
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experiments, and parametric investigations. The modelling component will be based, as much as possible, on semi-analytical thermo-mechanical formulations. This is to facilitate calculation accuracy, numerical
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section Energy Technology and Computer Science, where you will have around 20 colleagues with a mix of research and industrial experience. We work with research, innovation, technology implementation, and
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doctoral candidate who meets the following requirements: A background and strong interest in aluminum alloys, fatigue analysis, and numerical modelling is preferred. Experience with computer aided design
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related field Documented metagenomics experience Experience with writing and running data analysis scripts in a command-line interface Solid programming experience in Python Experience with scripting and
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experience with carbohydrate-active enzymes is prioritized. You must be well organized, structured, self-driven and enjoy interacting and collaborating with colleagues including PhD students, postdocs, and you
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for these types of experiments at the single cell level. Your primary tasks will be to: Design and conduct experiments to generate high-quality datasets Analyze and interpret complex datasets related to gene