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Field
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clinical features using machine learning and foundational modeling approaches. This work supports disease modeling across chronic kidney disease, acute kidney injury, cancer, and neurological conditions. A
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the appointment start date; demonstrate strong expertise in computational biology or data-driven modeling, with experience in one or more of the following areas: machine learning or deep learning, structural
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well as general research involving the application of methods from theoretical physics, mathematics, and machine learning with the goal to understand the brain function. Position Requirements Applicants
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scientists, and machine learning experts will be an essential and enriching component of the position. Strong candidates will have a background in machine learning and natural language processing (NLP), with a
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evidenced by a strong publication record in one or more of the following areas: random matrix theory, stochastic processes, neural networks, machine learning, and sparse data structures • Proficiency in
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management and planning skills; strong problem-solving and organizational skills; strong computer experience with Microsoft Office suite; and experience with or willingness to learn new laboratory management
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 1 hour ago
should have a strong background in data science, machine learning, remote sensing, wildfire science, or a related field. Experience with deep learning frameworks, satellite observations (e.g., Sentinel
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Computer Engineering or a closely related field, completed by the start date of the appointment. U.S. citizenship is required. Research experience in at least one of the following areas: ● Chip design
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human health. Within this mission, the Iorio Group works at the intersection of computational biology, functional genomics, and precision oncology, integrating machine learning, large-scale CRISPR