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are expected to orient more strongly towards hospital-at-home and strengthened collaboration with primary care and municipal services to support more integrated and coherent patient pathways. These developments
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(LLMs) to explore historical text data and cultural heritage collections. Collections of historical texts are increasingly used to train AI, but, consisting of highly heterogeneous text data
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dynamics (CFD) will be developed and coupled with the existing model to account for melt pool dynamics to include advection in the thermal modeling and to predict porosities and imperfection trajectories in
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. This project aims (1) to develop a predictive and robust thermodynamic framework that systematically evaluates molecular thermodynamic theories and integrates them into a unified platform capable of accurately
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Candidates (DCs). We aim to create a network of early-stage researchers equipped with knowledge and skills - including entrepreneurship – to develop and support implementation strategies that address
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understanding of molecular thermodynamics, and realize the importance of different types of properties in selecting and developing the most physically sound thermodynamic model for water and electrolytes
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under uncertainty”. This position is part of the ERC-funded DECIDE project lead by Professor David Pisinger. You will be responsible for developing new methods for decision support in stochastic
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power electronics to enhance the reuse and recycling of components, enabling a more circular life cycle. The work will contribute to a new paradigm in the development of power electronics that incorporate
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funded by the Novo Nordisk Foundation and led by Assoc. Prof. Janus Juul Eriksen @ DTU Chemistry – revolves around the development of new decompositions of molecular properties into local contributions
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to the development of background-suppression techniques for single-photon detectors used in axion experiments, operating at optical and infrared wavelengths. The research project includes the installation and