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the group's core research areas, and a proven ability to conduct independent, high-impact research. Experience in cybersecurity for cyber-physical systems, digital twins, BIM, AI and machine learning
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of Position Temporary Position Time Status Full-Time Required Education PhD or equivalent in biology or related field/9 years Required Related Experience Molecular Biology RESEARCH: Cell culture, animal work
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, ROS) Solid skills in numerical analysis Advanced knowledge of computer vision Experience in human–robot interaction Particularly Meritorious It is particularly meritorious if the applicant has: A PhD
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team-oriented interprofessional education to ensure a highly skilled workforce
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the application of statistics and machine learning in social science. The position requires no teaching, though teaching opportunities may be provided if requested. When teaching, successful candidates will carry
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of machine learning techniques, programming and coding for data analysis, biomarker discovery, and collaboration with clinicians and students. Additionally, the candidate will be responsible for grant writing
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position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description:Postdoctoral Researcher - Machine Learning for Plant Regulatory Genomics
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-physical systems, digital twins, BIM, AI and machine learning, robotics, or digital construction technologies is highly desirable. Strong programming and analytical skills, excellent written and verbal
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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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Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation