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Field
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for the physical sciences. We have a strong profile in computational statistics, simulation and learning algorithms, and scientific software development. As a closely collaborating, international team
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algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure, improved mechanical and corrosion properties. Research stays are planned
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groups are strongly encouraged to apply. Your Tasks: Development and application of algorithms for modelling, evaluation and visualization of ultrafast processes Investigation of ultrafast dynamics in
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to develop automated algorithms for downscaling drivetrain components for specific test purposes. Furthermore, you will perform multiple case studies to analyze the performance of the developed scaling methods
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with the latest sensors (camera and LiDAR sensors), is available for the work. What you will do Development of algorithms for 3D multi-object tracking based on heterogeneous sensor data fusion (standard
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Computational Biophysics/Chemistry (see also https://constructor.university/comp_phys ). The PhD position is focused on efficient algorithms for the simulation of non-adiabatic exciton transfer dynamics in light
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. This is because experimental techniques to solve structures of protein complexes favor more stable interactions with larger interfaces and because we lack efficient algorithms to compute similarity between
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for the discovery of new physics experiments) Developing, benchmarking and advancing state-of-the-art AI-driven exploration, optimization, and search algorithms in extremely complex and enormously large spaces
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exploration, optimization, and search algorithms in extremely complex and enormously large spaces motivated by physics and chemistry (RL, BO, Large-Scale Ansatze, …) AI-driven discovery of hardware for some of