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Field
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disease traits beyond the visible spectrum. Data Analysis and Computational Approaches – Introduction to AI-driven data analysis and machine learning for interpreting genomic and phenotypic datasets
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years. This role will develop and apply new machine-learning based approaches for extremely precise radial velocity studies and exoplanet spectroscopy with the NEID, HPF, and MARVEL facilities, and pursue
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Design for Learning. 5. A publication record in any of the following fields: disability studies, blind/low-vision education, science education, STEM education, instructional technology, or special
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neuroethology and robotics. This position focuses primarily on the neuroethology aspects of our research program, with particular emphasis on understanding the behavioral and neural mechanisms underlying active
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Science, Computational Biology, Bioinformatics, or a closely related field. Experience with computational modeling, statistical programming (Python, R, MATLAB), or machine learning. Experience working with large datasets
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and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning
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gain real-world experience through research, internships, and industry-sponsored capstone projects. With a versatile curriculum spanning software, systems design, nanofabrication, and machine learning
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
Engineering stresses the application of science and engineering, mathematical analysis, and computer techniques to biomedical problems. The research and entrepreneurship of the faculty, students, and staff aim
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for a postdoctoral researcher to join an experimental plasma physics program focused on high-energy-density and laser–plasma science. The successful candidate will contribute to the design, execution, and
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Experience Appropriate PhD in a related field. Preferred Qualifications Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in the environment