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reproducibility and facilitate future research. Qualifications: A successful candidate will be able to demonstrate some, or all, of the following skills: Proven practical experience with electron-beam lithography
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points) or a similar degree with an academic level equivalent to a two-year master's degree. Key Selection Criteria Hands-on experience in Synthetic Biology and Genetic Engineering is mandatory. Knowledge
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graph using RDF, OWL, and related technologies Designing and implementing workflows for data ingestion, integration, and querying across multiple systems Driving use-case studies that demonstrate
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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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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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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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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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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