61 computational-material-science PhD positions at Technical University of Denmark in Denmark
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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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candidates with a degree in materials science, solid state chemistry, electronic engineering or similar. Experience with one or more of the following areas is considered an advantage. Fuel cells 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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) 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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. 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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, 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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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