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focus on charge injection, ion transfer, and structural dynamics in realistic and model systems for battery materials. The position will span experimental efforts at large scale X-ray facilities, handling
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writing scientific papers. The developed models will be tested on data from energy investment models, as well as transport infrastructure problems. We will be an academic team of three PhD students and four
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, through developing predictive models and new experimental methods and instrumentation, to design creative and cost effective CO2 trapping processes. The need is urgent, the task is challenging and a
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performs theoretical, numerical, and experimental research in the field of manufacturing engineering. It covers a wide range of manufacturing processes and modelling approaches, metrology at all scales
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the experiments. You will also have the opportunity to carry out your own simulations with our numerical model. Qualified applicants must have: A strong drive to move the frontiers of science. Ample experience with
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models Tough bio-inks for surgical procedures We are looking for candidates with a high degree of independence and a strong drive for scientific excellence. These positions provide excellent opportunities
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for industrial decarbonization with emphasis in system development, modelling, optimization and validation, and focus on: Develop thermally integrated storage and conversion systems, including Carnot batteries and
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on regulatory mechanisms of cell signalling in several cellular models. The team combines omics technologies with bioinformatics, and functional validation of candidates by biochemical, cell biology, and imaging
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tasks are carried out in interdisciplinary collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved through a strong academic
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will benefit from Lonza’s expertise and technology within peptide T cell immunogenicity, and the vast expertise within immunoinformatics and machine learning models at DTU to address this challenge