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the carbon footprint of milk production. The project will apply advanced statistical methods, artificial intelligence, and cutting-edge genetic models to support and enhance management and breeding decision
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both technical insight into data modeling and a solid understanding of how real-world engineering data is generated, structured, and used. We are seeking motivated candidates with strong programming
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. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus
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Project MYC is a critical transcription factor in most cancers, where it cooperates with many different protein complexes to activate diverse pro-tumorigenic pathways. Together with a senior postdoc in the
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advancement and interdisciplinary collaboration, dedicated to solving the complex challenges of today's rapidly evolving engineering landscape. In line with our commitment to excellence and our mission
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conversion reactions. The second position is focused on modelling stability of electrocatalyst materials. The aim is to develop a framework to predict metastability of catalyst materials. Among the methods
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a team of 25 colleagues dealing with CCUS, and industrial partners in Denmark as well as abroad. Your primary tasks will be to: Apply AI in context of capture solvent modelling Understand and analyse
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Foundation Models initiative . The proposed starting date is 1 September 2025 or soon thereafter. The appointment will be made for a term of three years at a competitive salary and will follow the PhD study
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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of classical computers will require thousands, or even millions, of qubits. This creates a major engineering hurdle: interconnect complexity. Each qubit needs dedicated control and readout lines, which