This position will involve the design and development of novel AI methods, especially self-supervised learning techniques used for training large-scale foundation models, tailored for fundamental physics analyses. The successful candidate will have a strong interest in multidisciplinary and theoretical work, particularly across the areas of High-Energy Physics (HEP), astrophysics, cosmology, statistics, and machine learning. The candidate will work closely with Prof. Pettee, leading new research directions and supporting the cohesion and mentorship of the team. The work schedule is flexible and will be determined at the time of hire. This position is in-person and eligible for a partially remote schedule.
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Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree