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computational challenges. This PhD project will investigate novel registration strategies for ultrasound-derived musculoskeletal point clouds. The work will focus on developing geometry-aware alignment methods
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strong societal impact. Your responsibilities will follow the project scope described above and include laser design and development, experimental nonlinear optics, laser and frequency-comb
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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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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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(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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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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. 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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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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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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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