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snails; (2) assist in developing computational digital twin and machine learning simulations; (3) build and test robotic prototypes; and (4) undertake developmental work including data analysis and paper
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, spectropolarimetric inversion techniques, and machine-learning–based approaches, for the physical interpretation of solar images and spectral profiles. Special consideration will be given to applicants with experience
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or interest in the use of artificial intelligence, machine learning, or computational tools in behavioral and experimental economics is appreciated. Strong emphasis will be placed on demonstrated research
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Duke University, Duke Center for Jewish Studies Position ID: Duke-Duke Center for Jewish Studies-POSTDOC [#31172, 50961808] Position Title: Position Type: Postdoctoral Position Location: Durham
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, glioblastomas, colon cancer, and lung cancer. Advancing precision oncology through machine-learning models: We integrate multimodal patient data, including multiomic data and health record information, to develop
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for children. Applications will be accepted immediately and candidates will be considered until the position is filled. Please visit our website at https://nyuad.nyu.edu/en/about/careers/postdoctoral-and
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www.icord.org for more information. Additional information about Dr. Krassioukov‘s laboratory can be found at: http://icord.org/researchers/dr-andrei-krassioukov/. Work Performed: The postdoctoral fellows
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Programming experience (e.g., R, Python) and interest in machine learning approaches Doctoral degree (PhD or equivalent) in Education, Psychology, or a closely related field by the start date Knowledge, Skills
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to an advanced Laboratory Directed Research and Development (LDRD) project, "Machine Learning Steered EXAFS Fitting for Autonomous XAS Analysis," aimed at revolutionizing real-time analysis of X-ray Absorption
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, geolocation and AI-enabled communication and networking systems. In these roles you will undertake research centered on the intersection of networking, communications, geospatial methods and machine learning