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Attributes for Success: Bachelor's, master's degree, or PhD in Artificial Intelligence, Machine Learning, or related computing or physics field and up to 2 years of relevant experience, equivalent combination
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Fermilab. The University of Chicago has an inherently crosscutting and interdisciplinary structure that is very supportive of newly emerging research opportunities and is open to the possibility
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in the design and development of the detector upgrade. The LPC is also a major hub for Machine Learning and AI developments for particle physics. There is close and frequent collaboration with
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. Computational astrophysics is supported by access to high-performance computing through the Research Computing Center at the University and through connections to Argonne National Laboratory and Fermilab
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exoplanets. Computational astrophysics is supported by access to high-performance computing through the Research Computing Center at the University and through connections to Fermilab and Argonne National
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exoplanets. Computational astrophysics is supported by access to high-performance computing through the Research Computing Center at the University and through connections to Fermilab and Argonne National
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(sensing and simulations), and artificial intelligence/machine learning. Research areas of specific interest for the 2027 Chamberlain search include (1) cosmology, (2) direct searches for dark matter, 3
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experience in research incorporating Artificial Intelligence, Machine Learning or Quantum technologies are especially encouraged to apply. To be considered, those interested must apply through the University
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experience in research incorporating Artificial Intelligence, Machine Learning or Quantum technologies are especially encouraged to apply. To be considered, those interested must apply through the University
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other units on campus. Topics of interest include foundations and applications of artificial intelligence, machine learning, large language models, scientific AI and machine learning, data ethics and