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Field
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in computational science, machine learning, and experience with synchrotron data analysis are strongly encouraged to apply. Position Requirements PhD completed in the past 5 years or soon to be
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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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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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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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on physics analysis and artificial intelligence/machine learning (AI/ML). The successful candidate will contribute to the group’s broad physics program, which includes precision Higgs and Standard
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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 preferred. Apply online at https
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proposal development and preparation of high-quality publications in top computer security, privacy, embedded systems, sensing, and networking venues. ● Pursue research topics such as protecting
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collaboratively, and a compelling explanation of how humanistic methods will be used in the completion of the year-long project. Candidates are expected to hold a PhD in a humanistic field at the time of
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veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL | Opportunities for Veterans at Brookhaven National
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colloquia and workshops in the Center and Department of Art History; and teach one course each academic year related to DCADP. The Postdoctoral Instructor is required to be in residence at the University