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the Department of Energy Sciences. At the division, we conduct research in various fields, including research in design and optimization of turbomachinery, reactive fluid dynamics, multi-phase and turbulent flows
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dynamics, such as hidden Markov models or statistical jump models, affect the optimal decision-making process for an investor. Specifically, we aim to develop new methods for regime models, including
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consists of 18 research groups covering a wide range of mathematical disciplines – from pure and applied mathematics to numerical analysis and optimization, as well as mathematical statistics and machine
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while optimizing sequence properties. An emerging frontier focuses on designing proteins that act as templates for inorganic interfaces, forming symmetric oligomers that control inorganic material
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of proteins with near-atomic accuracy. Models such as RFdiffusion, LigandMPNN, and hallucination-based frameworks can now generate symmetric oligomers, cages, and backbones while optimizing sequence properties
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and the Faculty of Medicine in order to optimize the conditions for preclinical and clinical translational research, research strategies and development, as well as education on both undergraduate and
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the use of crystallographic software and data processing pipelines Experience working with computation clusters and managing large datasets Proven ability to develop, maintain, and optimize scientific