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of thick and strongly scattering samples. Optimize reconstruction algorithms for efficient large-scale 3D imaging, including high-performance and GPU-accelerated computing where appropriate. Design, optimize
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-design of morphology and control. This can involve optimizing robots through techniques from Evolutionary Robotics in a simulator and then deploying robots for further training and subsequent testing in
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receptor based on existing crystallographic data and perform molecular docking for ligand optimization • perform extensive molecular dynamics (MD) simulations (AMBER, NAMD, GROMACS) in fully hydrated
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group’s work is the optimization of the medication use of the individual, patient living with multiple long-term conditions. This also applies to the planned project. The postdoctoral project will
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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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institutions. The PhD Research Fellow will focus on enabling robust, intelligent robots through co-design of morphology and control. This can involve optimizing robots through techniques from Evolutionary
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pharmaceutical sciences. Practical (hands-on) experience with preformulation studies or formulations optimization, particularly liposomes. Documented fluency of in English and be able to work in an international
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of protein or metamaterial structures, the development of effective architecture for machine learning classification of the structures, and reinforcement learning methods for optimizing the structures
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work will include: Solid state and wet-chemical synthesis routes and fabrication of novel, complex functional oxides with properties optimized as selective oxygen carriers advanced characterization
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that integrate prediction and control algorithms, optimizing data transformations, offloading and distributed computing, and exploiting mechanisms such as network slicing and multi-access edge computing