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of Copenhagen and also involves partners at the McGill University (Canada) and the Department of Physics at DTU. The goal is to replace the highly inefficient current fertilization practices by a revolutionary
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, you will contribute to research-based teaching and the supervision of student projects. Skills in mathematical modelling and machine learning of relevant physical glacier processes (ice sheet and
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tools for production of proteins and peptides using yeast. The project aims to establish a robust and efficient production process for yeast based CFPS extracts through a collaborative effort that
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them to develop preforms; Draw the multifunctional optical fibers based on modified thermal drawing process of multiple materials (e.g. polymers and metals) with strongly different thermomechanical
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to relevant external sources. By enabling data interoperability across facilities and process units, this infrastructure will allow real-time coordination, intelligent scheduling, resource sharing, and improved
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include: Skills in mathematical modelling and machine learning of relevant physical glacier processes (ice sheet and mountain glaciers), with proficiency in MATLAB/Python/Fortran, and related software tools
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. The technologies include fuel cells, electrolysis, power-to-x, batteries, and carbon capture. The research is based on strong competences on electrochemistry, atomic scale and multi-physics modelling, autonomous
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PhD students and postdocs at DTU Energy and DTU Physics, which will realize your designs in the lab, provide experimental input to your modelling and ultimately use the sensors to detect the activity in
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for light trapping in thin-film solar cells .” You will become part of an enthusiastic team working closely with collaborators at DTU Physics and DTU Nanolab to advance neural network-based methods
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communication skills in English, both written and spoken. As a formal qualification, you must hold a PhD degree in physics, chemistry, materials science, nanoscience or equivalent. We offer DTU is a leading