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in machine learning and artificial intelligence Experience with numerical analysis and scientific computing Knowledge of power systems and renewable energy technologies Experience in power system
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science applications Computational Atomic-scale Materials Design with a focus on materials modeling and discovery with electronic structure calculations and machine learning Luminescence Physics and
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of code to utilize GPU-acceleration on DTU’s high-performance computing cluster or other HPC systems. You will also analyze realistic physical implementations of the architectures you explore, with a
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, building energy and installation, solid mechanics, fluid mechanics, materials technology, manufacturing engineering, engineering design and thermal energy systems. Technology for people DTU develops
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. You should have a strong academic background in engineering, applied mathematics, or computer science, combined with a clear interest in scientific programming, machine learning, and data analytics
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We are seeking an outstanding candidate for a PhD fellowship in the field of computational fluid and solid mechanics. The fellowship will start on September 1st, 2025, or as soon as possible after
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) therapy on the biology of γδ T cells and how can we use this knowledge to help us predict the success of therapy and prevent the development of side-effects. Position 1 will focus on the cellular and
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background in Computer Science, Informatics Engineering, Mathematical Modeling, Computational Urban Science, Transport Modeling or equivalent, or a similar degree with an academic level equivalent to a two
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. The overarching goal of this newly funded project is to realize quantum light sources coupled to quantum memories. Quantum memories are key components of optical quantum computers and scalable quantum networks