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inference and statistics; computer vision and novel applications of machine learning.Advanced knowledge of R or Python is required. Intermediate knowledge in C/C++ and/or at least one SQL dialect is
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-Sigler Institute for Integrative Genomics and the Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning
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Posting Description POSTDOCTORAL ASSOCIATE, Mechanical Engineering, to perform cutting-edge research on projects centered around machine learning models for Computer Aided Design and Engineering
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significant mathematical and computational background to learn and develop new AI methods. While demonstrated experience in computer vision and deep learning for pathology or other biomedical image analysis is
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benefits package, including health and life insurance, generous paid leave and retirement programs. To learn more about UofSC benefits, access the "Working at USC" section on the Applicant Portal at https
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on Just and Equitable Cities (https://centerforcities.aap.cornell.edu/initiatives/overview ). We invite applications from candidates who will have completed their Ph.D. degree no earlier than September 1
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and societal. In this context, we welcome applicants from diverse backgrounds such as computer science, electrical and computer engineering, sociology, public policy, information science, communication
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candidates with strong expertise in Bayesian methods, uncertainty quantification, and/or machine learning applied to nuclear theory. The group’s research spans a wide range of topics including nuclear
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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, machine learning techniques, and cosmological simulations. The group is actively involved in multiple JWST Guaranteed Time Observation (GTO) and General Observer (GO) programs, an upcoming Large Program on