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electronic structure theory (e.g., density functional theory), and machine learning based computational studies of molecular and periodic systems. The postdoc will also work within a multidisciplinary multi
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imagery). Experience in building data models using Python or other statistical and/or mathematical programming packages. Proficiency in developing machine learning algorithms to analyze spatial-temporal
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strategies. The candidate will join the Machine Intelligence Group for the Betterment of Health and the Environment (MIGHTE) led by Prof. Mauricio Santillana. MINIMUM QUALIFICATIONS PhD in a quantitative field
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to join our team. Our lab focuses on developing and applying innovative statistical machine learning methods, single-cell multi-omics, and systems immunology approaches to investigate immune-mediated
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(IDP), conduct research studies, attend required courses/seminars, write grants, publish manuscripts, present oral presentations locally and nationally, and learn other skills necessary for a successful
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Pythonis; and experience with tokamak physics or machine learning techniques. The appointment will be for two years with the possibility of renewal based upon satisfactory job performance. Application
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PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets Experience in statistical or scientific programming (ideally R and/or
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in solid mechanics framework Experience in non-linear solid material response and fracture modeling Experience in machine-learning modeling for solid mechanics applications Experience in
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machine learning, Computer vision, Swarms, Autonomous Robots, hardware security, and Embedded systems development is desired. The successful applicant will work on various projects on robotics and computer
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or commensurate with experience Type of Position Student Position Time Status Full-Time Required Education PhD or MD Required Related Experience Biomedical Sciences Required License/Registration/Certification NA