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Field
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involves analyzing data obtained by cosmological surveys such as DESI, Euclid, Roman and others, developing new methods and algorithms, supporting other group members in particular graduate students, and
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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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: Apply Position Description Experience Required: Entry-level (PhD Program) or Experienced (Postdoc, Faculty, Scientific Lab, Finance Industry) Education: PhD in Math, Science, Engineering and other
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candidate will design and develop digital twin algorithms for computational fluid dynamics, contributing to innovative solutions in healthcare software systems. This role involves collaboration with research
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both fundamental and applied research, from the development of algorithms, tools, and frameworks that advance scientific discovery to methodologies that utilize computational approaches to generate
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 23 hours ago
Position Information General Information Position Number POST40 Working Title Postdoctoral Fellow - Computer Science Division Academic Affairs Department Coll of Computing&Informatics (Col) Work
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Status: Nonexempt Work Schedule: Flexible Summary The intern will receive training on machine learning algorithms, implementing them, and fitting them on the datasets in our cluster computers. Overall
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writing C++ and PyTorch. Training and debugging RL agents. Imitation Learning algorithms for robotics or autonomous vehicles. Prior work combining RL with human data or feedback. A track record of code
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) Ph.D. (or foreign equivalent) in Electrical Engineering, Computer Science, Applied Mathematics, or a closely
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a motivated individual to support research and development tasks relating to algorithm development and data analytics requiring a background in the geosciences and data sciences. This includes tasks