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-solving person with a strong background in bioinformatics and previous experience with next-generation sequencing (NGS), ideally in cancer genetics. In particular, familiarity with the analysis of whole
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), to work on problems at the intersection of biology, medicine, mathematics and computation. The successful candidate will contribute to the development of next-generation learning algorithms to understand
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approaches, such as topology optimization, with gradient-free methods, such as genetic algorithm, in order to exploit the specific strengths of the two classes of algorithms, and through this reach an ideal
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verification algorithms and prototypes on large microgrids, Naval systems, and utility systems. ● Assist grant proposal writing, work collaboratively with industry and government, and mentor graduate
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, genetics, and population health, working closely with collaborators at the Nuffield Department of Population Health (NDPH), the Big Data Institute (BDI), and the Department of Psychiatry. You will develop
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developments, algorithmic implementation, and analysis. Experience with electronic structure and dynamics, non-adiabatic molecular dynamics, and coding is strongly selected for. Please seehttps
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implement algorithms, models, and software applications that can be translated to clinical use. Job Description Primary Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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structure-preserving discretization algorithms (a refinement of finite-element analysis compatible with exact geometric, topological, and physical constraints) with artificial neural networks for achieving
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working under the supervision of Prof. Jaideep Vaidya (the PI and Director, I-DSLA) to develop and analyze privacy-preserving solutions for biomedical data research, implementing the developed algorithms