661 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions in United States
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Field
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), Kinetic Modeling. Machine Learning Interatomic Potential (MLIP) accelerated simulations. Demonstrated ability of coding in Fortran, Shell, or Python with development experiences. Deep knowledge in excited
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the global health scenario and domestically for dissemination, and plenty of opportunities for career advancement. •Learn background/research methods of studies for which analysis is conducted with limited
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astrophysics, exotic core-collapse supernovae, and machine learning methods for time series analysis. A PhD in Physics, Astronomy, or a closely related field is required. The position will entail work on a
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time of hire is required, along with a strong theoretical or practical background in statistical mechanics, quantum dynamics, or Machine Learning. Demonstrated experience operating and maintaining a
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. QUALIFICATIONS PhD in Civil Engineering, Environmental Science, Computer Science, or a related field Research experience in hydrology, geospatial analysis, and machine learning Skills of scientific writing and
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Computer Engineering or a closely related field, completed by the start date of the appointment. U.S. citizenship is required. Research experience in at least one of the following areas: ● Chip design
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affiliates reflect strengths in machine learning, biological modeling, data ethics, data sovereignty, computer science, environmental data science, climate change policy and modeling, evolutionary genetics
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, biophysics, or in a related interdisciplinary field. Experience with AI and machine learning tools is preferred. Applicant instructions: Applicants should be prepared to upload the following documents when
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. Candidates whose doctoral work focused on deep learning methods and who have a strong interest in genomics will also be considered. Experience: At least one publication in computational genomics or machine
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We are seeking creative Postdoctoral researchers to bridge the gap between leadership-class supercomputing and cutting-edge open science in the area of AI and Machine Learning. Successful candidates