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to this search are candidates with expertise ranging from NeuroAI, machine learning, and artificial intelligence to brain-body interactions, including cancer neuro and neurodegenerative disorders, and systems and
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, developing and applying advanced computational methods to study cosmic structure. The project is funded by a Simons Foundation grant and is part of the international collaboration Learning the Universe
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applications for a Tenure Track (TT) position in the area of physics, with a specialization in the development and implementation of techniques of Artificial Intelligence (AI) and Machine Learning (ML) across
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candidates with expertise in discrete mathematics, with particular interest in candidates whose research advances the mathematical foundations of artificial intelligence, machine learning, and quantum
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candidates with expertise in theoretical foundations of artificial intelligence, including statistical/machine learning theory, optimization, and deep learning. Successful candidates must have a strong record
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and computational methodologies, including those pertaining to data science, scientific machine learning, and optimization. Of special interest are candidates whose work could support RPI's initiatives
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starting on, or after, 7/01/2026. The position is to be offered jointly with the Center for Computational Astrophysics (CCA) at the Simons Foundation Flatiron Institute in New York City. The successful
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). Of particular interest to this search are candidates with expertise ranging from NeuroAI, machine learning, and artificial intelligence to brain-body interactions, including cancer neuro and neurodegenerative
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to support the Flatiron Institute; Founders-Directed; Science, Society & Culture; and Simons Foundation International grantmaking divisions. You can learn more about working at the Simons Foundation
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theoretical foundations of artificial intelligence, including statistical/machine learning theory, optimization, and deep learning. Successful candidates must have a strong record of research and teaching and