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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
: * Introductory proficiency in Python, R, or another programming language * Prior exposure to machine learning or AI techniques in clinical research * Experience using deep learning frameworks * Familiarity with
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) at the University of Florida (UF) is seeking a highly motivated and ambitious Postdoctoral Researcher with a strong background in Artificial Intelligence and Machine Learning (AI/ML). This is an exciting opportunity
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. The Postdoctoral Associate will apply his/her technical skills toward development and implementation of machine learning, computer vision, and other algorithms for analysis of medical images and prognostication as
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include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow
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plus Education and training PhD in Bioinformatics or in Biology, Machine Learning, Statistics, Physics, Mathematics, Chemistry or related areas Languages: Highly proficient in both spoken and written
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molecular biology skills; proficiency with standard word, statistical, and imaging processing software (e.g., Microsoft Word, GraphPad Prism, Adobe Illustrator). Job Duties Job Duty Implement genetic, cell
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also include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a
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Education and Experience Preferred experiences include research in cognitive neuroscience, human functional brain imaging, psychology, neurology, psychiatry, machine learning, data visualization, and data
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must have submitted their PhD thesis for evaluation by the closing date of this announcement. Strong experience in using MRI to study brain structure. Extensive experience with machine learning in image
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The Rantalainen group is focused on application of machine learning and AI for development and validation of predictive models for cancer precision medicine, with a particular focus computational pathology. Our