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in the United States. Preferred methodological skills include statistical analysis of survey and other large-n data, qualitative interviews, and/or text analysis and machine learning skills
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will develop novel machine learning and artificial intelligence (ML/AI) methods for genomics data, especially: large-scale single-cell genomics data, high-definition spatial genomics, digital pathology
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accelerators including TrueBeam machines – all with onboard kV/MV radiograph/CBCT for IGRT and gated treatment, Halcyon, Ethos, large-bore CT simulators, PET/CT, MR unit, HDR units, ARIA information system, and
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efficiency. Experience working with R or Python data science tools to analyze and visualize health care data and to develop data pipelines to support machine learning model development. Experience working with
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, establishment of a seagrass farm, and monitoring of a large living shoreline project. In addition to research, the post-doctoral scholar will be required to teach a 4-5 week-long field course each spring semester