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of computational biology, Genomics, machine learning, and data science, contributing to the development and evaluation of advanced algorithms for analyzing large-scale biological datasets. This role is ideal
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that combines modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks
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large amounts of geospatial training data to effectively classify grazing, haying, and other grassland management regimes on U.S. agricultural lands. The researcher will also work closely with colleagues
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/Statistics Internal Number: JR101137_1774276539 The Data Science and Statistics Program at the University of Richmond invites applications for a two-year postdoctoral research position in the Distant Viewing
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behavioral clinical trials focused on pain, symptom management, and health promotion in patients with cancer and other chronic diseases. Current projects range from pilot studies to large trials, including
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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of large-scale biological datasets, applying statistical modelling and computational approaches to high-dimensional data such as bulk and single-cell sequencing, gene expression, proteomics, or metabolomics
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. in computer science or a related field and will have prior experience collaborating with large, interdisciplinary teams. The candidate will be a strong self-starter who is capable of both working
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). Remedies and complaint filing deadlines vary by program or incident. Persons with disabilities who require alternative means of communication for program information (e.g., Braille, large print, audiotape
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time of appointment. Demonstrated expertise in bioinformatics, statistics, microbiome data analysis, and/or computational methods. Experience working with large population-level datasets (e.g., NHANES