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programme, please see DTU's rules for the PhD education . Assessment The ideal candidate will have solid background in experimental molecular biology combined with experience with microbial protein production
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design and processes, building construction and safety, building energy and installation, solid mechanics, fluid mechanics, materials technology, manufacturing engineering, engineering design and thermal
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candidates with a degree in materials science, solid state chemistry, electronic engineering or similar. Experience with one or more of the following areas is considered an advantage. Fuel cells and
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in machine learning and artificial intelligence Experience with numerical analysis and scientific computing Knowledge of power systems and renewable energy technologies Experience in power system
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of code to utilize GPU-acceleration on DTU’s high-performance computing cluster or other HPC systems. You will also analyze realistic physical implementations of the architectures you explore, with a
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, building energy and installation, solid mechanics, fluid mechanics, materials technology, manufacturing engineering, engineering design and thermal energy systems. Technology for people DTU develops
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science applications Computational Atomic-scale Materials Design with a focus on materials modeling and discovery with electronic structure calculations and machine learning Luminescence Physics and