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Demonstrated research experience in computational physics, machine learning, or related areas. Practical experience in developing novel AI/ML models and algorithms. Experience collaborating in multidisciplinary
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will be part of a team that already uses machine learning to improve online accelerator models and that develops correction algorithms for accelerator operations. This position is for a 2-year research
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high intellectual merit and the willingness to use machine learning and/or AI techniques. Essential Duties and Responsibilities: Successful candidates are expected to develop an impactful research
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physics. Development of new artificial-intelligence and machine-learning techniques for high-energy and nuclear physics. Close interaction with our collaborators in the EIC and the BNL theory group will be
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in real-world environments. Position Description: The CFN is seeking an exceptional researcher to pursue frontier research in artificial intelligence and machine learning (AI/ML) to advance scientific
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analysis of atmospheric numerical model output (e.g., WRF, PALM, SAM) Experience with machine learning and artificial intelligence techniques Experience with predictive modeling Environmental, Health
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research environment. Self-motivated, with a strong ability to learn quickly and adapt to new challenges. Preferred Knowledge, Skills, and Abilities: Experience with high-volume scientific data collection
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scientific and security problems of interest to Brookhaven Lab and the Department of Energy (DOE). Topics of particular interest include novel development and application of machine learning models, especially
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control under high inverter-based resources (IBRs). • Develop and apply artificial intelligence (AI)/machine learning (ML) techniques for power system planning, operation, control, and cybersecurity
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post-doctoral research associate position in machine learning (ML). This position offers a unique opportunity to conduct both basic and applied research in concert with collaborators working on diverse