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Field
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. Apply advanced statistical, econometric, and/or machine learning methods to analyze complex health datasets (e.g., claims, EHR, hospital discharge, survey data). Prepare manuscripts for peer-reviewed
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pension 29 days annual leave plus bank holidays, along with Christmas closure Ride to work and EV car scheme available For more information, please see University of Manchester Benefits . You can also find
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of Computer Science at UNNC is developing research excellence in areas including Machine Learning, Big Data, Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and
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. Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading scientific journals
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streams with perturbation signatures and fit these. For these fits, we will explore the speed up from using GPUs as well as machine learning techniques, e.g. simulation-based inference. Finally, we will use
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imaging science or related field or an equivalent qualification; (ii) demonstrate research skills in imaging science and machine learning, particularly on image reverse engineering, fake image and video
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Engineering, Computer Engineering, HealthTech, MedTech, Product Development, Clinical Engineering or related disciplines with relevant experience in engineering, prototyping, product development or healthcare
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at NCAUR: https://www.ars.usda.gov/midwest-area/peoria-il/national-center-for-agricultural-utilization-research/mycotoxin-prevention-and-applied-microbiology-research/ Learning Objectives: Under the guidance
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Informatics (DBMI) at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Research Fellow with experience in machine learning and scientific programming. The candidate will work with a multi
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data integration and analysis Integrate phylogenomic and functional data using machine-learning approaches for candidate gene prioritisation Contribute to software and web-tool development Present