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Field
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techniques. The research will integrate ab initio-based modeling and DFT calculations with experimental data to enhance the understanding and optimization of the proposed materials as sorbents or possible
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such as PyTorch and TensorFlow. Experience with high-performance computing and/or scientific workflow. Strong background in inverse problems, numerical optimization and image processing. Job Family
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complex endometrial models and optimizing in vitro implantation assays. Culturing human embryos and generating stem cell-based embryo models. Tissue sectioning for advanced spatial transcriptomic analysis
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modeling tools to support outbreak response, optimal vaccine strategies, and understanding key epidemiologic questions. This NIH-funded project is conducted in collaboration with the California Department
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experience. Research background in decision making systems, in particular the use of different optimization, machine learning, and decision making modeling techniques for problem solving. Desire to grow
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- and socially- vulnerable populations and/or b) improving healthcare delivery (i.e., from providers and within the medical system) to optimize healthcare outcomes of women with uterine fibroids
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with optimization techniques and accelerated computing are a plus for this position. Strong written and spoken English skills are required. The successful candidate will: (1) develop novel methodologies
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, safety, and compliance. Perform preventive maintenance on laboratory equipment to keep them in optimal working condition. Conduct experiments related to identifying metabolites in plant and biological
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: (1) Conducting high fidelity CFD simulations of combustion, heat transfer, chemical reactions, and phase change phenomena in industrial processes using commercial software. (2) Optimizing existing in
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Responsibilities Research: - Conduct research in AI reasoning, semantic modeling, and knowledge graph development. - Develop and optimize graph databases for structured knowledge representation. - Apply neural