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Field
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, physics, computer science or related discipline. Experience: Python programming for scientific applications. Experience with AI/ML algorithms. Technical Knowledge Skills: Computer programming, particularly
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evaluation of machine learning, computer vision, and other algorithms, primarily in the context of health. They will be part of the thriving research community of Duke Spark (spark.duke.edu) where AI
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and efficiency of life sciences research. Developing the algorithms, infrastructure, and governance necessary for such analysis can simultaneously enhance hypothesis generation, computational modeling
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-omic molecular profiling, including genetics, transcriptomics, microbiomics, metabolomics, and immune system markers. The division leverages this data and advanced AI, medical, and computational models
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for platforms such as Instagram Reels, TikTok, and YouTube Shorts. Knowledge of current social media trends, platform algorithms, audience engagement strategies, and digital marketing best practices. Excellent
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of teaching and successful reappointment), and regular, generously funded, post-tenure sabbaticals. Support for teaching, grant submission, computing software, and community partnerships in courses is available
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bioinformatics, computational biology, biology, genetics, computer science, statistics, applied mathematics, physics or a related field. Strong programming skills in Python, R, C/C++ or similar, with experience
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 12 days ago
, storing, disseminating, and translating data into actionable insights. * Algorithms and Models: Mathematical, computational and statistical tools that empower researchers and stakeholders to discover
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 5 days ago
, storing, disseminating, and translating data into actionable insights. * Algorithms and Models: Mathematical, computational and statistical tools that empower researchers and stakeholders to discover
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transportation contexts, and machine learning classifiers Heuristics & Solvers: Develop and refine custom heuristics and metaheuristics (e.g., Tabu Search, Genetic Algorithms) to find high-quality solutions