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Field
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experience in large-scale structure simulations, working knowledge of applications of machine learning techniques in cosmology and/or astrophysics (in particular simulation-based inference), strong programming
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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental
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significant impact on the world around us. Carnegie Mellon University’s department of Electrical and Computer Engineering is looking for a talented postdoc/research scientist to work on an innovative project
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SURGERY (06740A) Is this split and/or fully grant funded? Yes Duties and Responsibilities A postdoc position is available in Dr. Gahtan’s lab at the Burn and Shock Trauma Research Institute in the Stritch
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++, or JavaScript Experience with AI or machine learning techniques, including large language models or agentic systems Experience developing or integrating interactive visualization systems, including web-based
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noise, a prototype cryogenic interferometer, using machine learning for nonlinear feedback control, devising techniques to quell opto-mechanical instabilities that can disable the interferometers, and
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models motivated by biological and therapeutic applications are particularly encouraged to apply. Expertise in statistical or machine-learning methods is also welcome, as connection with experimental and
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postdoc with interests in RNA virology and host-pathogen interactions. For detailed information about the laboratory’s research, see our website (http://www.mouncelab.com). Experience in molecular virology
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. This project provides a vibrant learning environment for all the trainees. The PI is committed to the professional development of the postdoc associate in addition to their technical excellence. Core
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales