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Field
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Qualifications A Ph.D. in fundamental physics or a relevant field, such as mathematics, statistics, atrophysics, or computer science. This position does not require any teaching. Essential Skills and Experience
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Oak Ridge National Laboratory, Mathematics in Computation Section Position ID: ORNL-POSTDOCTORALRESEARCHASSOCIATE3 [#27208] Position Title: Position Type: Postdoctoral Position Location: Oak Ridge
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scholarly sector. AI3 includes more than 70 faculty members with interests ranging from novel algorithms, architectures, and mathematical / ethical foundations to applications in art, biological sciences
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commuting to the assigned work location when necessary. Qualifications We Require: PhD in engineering, physics, applied mathematics, computer science or other relevant field Ability to obtain and maintain a
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) Mathematics and Statistics (10 ) Other Non-Science & Engineering (13 ) Physics (16 ) Science & Engineering-related (1 ) Social and Behavioral Sciences (29 ) Age: Must be 18 years of age Veteran Status
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venuesStrong programming skillsSolid mathematical foundation, including linear algebra, probability, statistics, and optimizationBroad and in-depth experience with machine learning algorithms and deep learning
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Science Statistics / Biostatistics Applied Mathematics Data Science Demonstrated expertise in modern machine learning, including at least one of the following: Deep learning (e.g., transformers, sequence models
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, societal, and scholarly sector. AI3 includes more than 70 faculty members with interests ranging from novel algorithms, architectures, and mathematical / ethical foundations to applications in art
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to contribute to innovative, policy-relevant research at the intersection of statistics, infectious diseases epidemiology, and global health. Appointment Details The successful applicant will be registered
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Geosciences, Environmental sciences, Civil or Environmental Engineering, Physics or Mathematics or a related discipline Experience in programming (e.g., Python, MATLAB, or similar), interest in machine learning