774 machine-learning-"https:"-"https:"-"https:" Postdoctoral positions in United States
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and stress level is moderate to high. Noise level is quiet to moderate. Physical Activities Ability to work in front of a computer for extended periods of time. Occasionally required to move about the
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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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to the development of remote sensing algorithms, simulation and modeling capabilities, and artificial intelligence/machine learning (AI/ML) methods in support of the goals of the joint NASA/USGS Landsat mission
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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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in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
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SPECIFICS Postdoctoral Scholar (Machine Learning or Artificial Intelligence in Molecular and Cellular Biology) The National Synthesis Center for Emergence in the Molecular and Cellular Sciences (NCEMS
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. Candidates will collaborate closely with interdisciplinary research groups advancing materials discovery through the convergence of computational chemistry, machine learning, and agentic science. This full
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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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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