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quality and consumer satisfaction. You will also apply statistical and machine-learning tools to explore how physical and chemical fiber parameters relate to dye uptake behavior, dyebath exhaustion, color
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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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the computational task: first-principles active-site descriptor models, high-throughput screening with machine-learned interatomic potentials, and a dedicated catalysis database. This position is ideal for a
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statistical software & machine learning (e.g., R, Python, SAS, or STATA). Experience working with large population dataset (e.g. EHR, claims data). Background in health informatics, population health research
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/or oceanography; or experience working with numerical simulations, large data, scientific programming, and/or machine learning. Applicants are asked to send a CV, a brief statement of research
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to excellence in research, education, and patient care. Learn more about Duke University's competitive benefits package. Research Areas Include Immune mechanisms of response and resistance to glioblastoma
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generating fusion energy. This research will focus on the chemical speciation and transport of tritium in the molten salt blankets using ab initio quantum simulations, machine learning potentials, and
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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of Energy (DOE) experimental facilities. This role involves research and development spanning areas such as optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high
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. Position Overview The successful candidate will develop and apply advanced computational and machine learning methods to large-scale genomic, clinical, and imaging datasets, working across one or more of the