31 structures-"https:" "https:" "https:" "https:" "https:" positions at Technical University of Denmark
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in the group of Niels Engholm Henriksen (https://www.kemi.dtu.dk/english/research/physical-chemistry ). You must have a solid foundation and interests in quantum chemistry, applied mathematics
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DTU Energy at https://www.energy.dtu.dk/ If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark . Application procedure Your
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, this PhD position might be the right fit for you! You will develop methodology for sustainability assessment of aggregate resource use in the construction sector applying a dissipation perspective on the
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is part of the MET2ADAPT Doctoral Network (Meta-Materials and Meta-Structures for Adaptable, Resilient and Sustainable Renewable Energy Power Plants), a prestigious Marie Skłodowska-Curie Doctoral
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Further information may be obtained from professor Ole Baltazar Andersen, phone : 45 45259754 oa(at)space.dtu.dk or professor Per Knudsen pk(at)space.dtu.dk You can read more about the division at https
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information may be obtained from Daniel Olesen, danole@space.dtu.dk or Michael Schultz Rasmussen, msr@space.dtu.dk You can read more about the division at https://www.space.dtu.dk/english/research
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are driven by curiosity, impact, and a shared commitment to advancing resource-effective solutions in construction and production. We look forward to welcoming a new colleague who will contribute
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obtained from Senior Researcher Bjarke Eltard Larsen , https://orbit.dtu.dk/en/persons/bjarke-eltard-larsen . You can read more about Department of Civil and Mechanical Engineering at www.construct.dtu.dk
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role will be vital to the success of the newly established DTU Arena for Life Science Automation (DALSA; https://dalsa.dtu.dk/ ). Together with a multidisciplinary team, you will implement DALSA’s
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sequence analysis Single cell analysis Protein structure prediction Cancer multiomics analysis Genotype to phenotype mapping You are expected to contribute to strengthen the deep learning focus