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properties under decompression or are even directly synthesizable at ambient conditions. We will use density functional theory based calculations, machine learning based techniques and work in close
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of Computer and Information Science, and the STING partner sites. You should enjoy working as part of a team and be willing to learn from your co-workers and share your knowledge and experience with them in
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modeling, optimization, and reinforcement learning; prior experience with EU projects is a plus. The workplace The Department of Computer and Information Science was founded in 1983 but its roots go back to
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Science, Data Science, Physics, Engineering or Biomedical Sciences or similar. You have a strong interest in machine learning and image analysis. Previous experience with deep learning is a necessity for these
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Machine learning methods High performance computing Multivariate analysis As a person, you are self-motivated and structured. You easily adapt to changing circumstances and find it easy to cooperate with
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interactions and phonon renormalization in different materials. To accelerate the simulations, we also expect the application of some machine learning approach. As postdoc, you will principally carry out
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the two. Providing validity arguments by linking decisions and validated actions with explanations within machine learning based systems in presence of adverse scenarios. Integration of industrial use cases