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observations from the Kepler and TESS satellites, complemented by Gaia data and ground-based spectroscopic and spectropolarimetric observations. See more information here: https://www.space.dtu.dk/english
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to enhance imaging quality and speed Creating efficient data acquisition and processing workflows for large datasets of skin nanotexture images Optimizing hardware-software integration for robust performance
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at DTU Bioinformatics is focused on bioinformatics and computational analyses of large amounts of data generated within biological, biomedical and biotechnological and life sciences area. We strive to gain
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of experience with research on fish diseases, and a large international network. The section is the National reference laboratory on fish, crustacean and mollusc diseases, and EU reference laboratory on fish- and
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of harnessing the potential of biological systems. Big data approaches and analysis of biological systems are key research instruments at the Centre. DTU Biosustain utilizes these advances for microbial cell
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. Quantifying circular economy strategies for wind turbine rotor blades, including reuse, recycling, and feedback loops. Assessing the climate mitigation potential of circular construction materials through data
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of meteorological phenomena impacting the wind energy sector, in particular with respect to wind resources and wind conditions. For example, investigating how large-scale wind farm clusters may impact atmospheric and
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with advances in automation, analytics and data science, has fundamentally changed the scope and ambition of harnessing the potential of biological systems. Big data approaches and analysis of biological
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PhD degree (or equivalent) in Manufacturing Engineering, AM, or related field Experience with metrology of small to large scale laser-based metal AM components (e.g. DED, powder-bed fusion) Experience
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oxygen delivery—without relying on human donors. You’ll build on the 3Bs group's extensive data and recent publications to evaluate the biological performance of these nanocarriers in preclinical models