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structures, the development of effective architecture for machine learning classification of the structures, and reinforcement learning methods for optimizing the structures for particular applications
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therapy. The project will involve both physics-based forward modeling of protein structures and reinforcement learning methods for optimizing the structures. The outcome from the models will be tested in
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Entropy Alloy (HEA) compositions suitable for Additive Manufacturing (AM) Develop a multiscale methodology to select compositions and microstructure with optimized fraction Establish and optimise Powder Bed
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algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML
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of the structures, and reinforcement learning methods for optimizing the structures for particular applications. An underlying motivation is to understand the internal representations developed by the machine
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The position belongs to the research group for clinical pharmacy , and is funded by the Norwegian Pharmacy Foundation. The main focus of ’the research group’s work is the optimization of the medication use
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rich contextual measures of psychosocial environments, SISU and PRISM characterize families and schools optimal for psychological development in a global crisis. Our explanatory variables of interest
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for Addiction Research Apply for this job See advertisement About the position We invite applications for a PhD Research Fellow position in Computational Structural Biology is available
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structures and reinforcement learning methods for optimizing the structures. The outcome from the models will be tested in experimental setups requiring deep understanding of protein chemistry and molecular
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addresses a key gap in current industrial practice, namely the lack of formal system models that integrate structural specifications with spatial and temporal behavior. Building on the Information Modeling