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to DTU’s PhD programme can be found here while the details for the enrolment and admission to DTU’s PhD programme are available here Solid background in Structural Dynamics, Finite Element Modelling and
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holistic multi-hazard risk framework capturing cascading effects across systems and scales; (2) the creation of digital environments utilizing real-time data for dynamic risk evaluation; (3) the advancement
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materials built by covalent linking of monomers, supramolecular polymers are dynamic and formed by the self-assembly of monomeric units brought together by non-covalent interactions. The connections between
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, interdisciplinary approach aims at relating the atomic-scale structure, dynamics and functions of single nanoparticles in both thermal catalysis and electrocatalysis, aiming to advance the understanding of catalysis
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that merge thermo-fluid dynamic laws, deep learning, and experimental data. A central goal is to overcome current limitations in TES operation and optimization, enabling discovery of new high-performance and
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partners are: Visibuilt (a start-up company), DTU Sustain, and Munck Asfalt (a road construction company). Project description and tasks This PhD project includes a combination of modelling, coding, field
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restraint conditions. A key goal is to develop both a sensor system and a prediction model for the short- and long-term deformation behaviour of concrete. These tools will be applied to full-scale structural
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experience with carbohydrate-active enzymes is prioritized. You must be well organized, structured, self-driven and enjoy interacting and collaborating with colleagues including PhD students, postdocs, and you
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global water contamination through advanced materials science. Your Role: Investigate the structural and chemical dynamics of molecular adsorption processes using advanced characterization techniques
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Job Description You will join a supportive and dynamic research team working at the intersection of machine learning and operations research. Your main task will be to design and implement ML