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data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the curious to deliver work
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and analyzing large secondary datasets, including but not limited to administrative claims data, electronic health records, national surveys, and disease registries. The applicant should have advanced
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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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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
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include designing and executing experiments to interrogate host-microbe interactions, analyzing and interpreting microbiome sequencing and/or metabolomics data, developing novel computational or analytical
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undergraduate or graduate students, if appropriate. Additional Information The ideal candidate should be an independent, solution-oriented thinker with a strong background in processing very large data sets
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, or related disciplines. Expertise in computational genomics, functional genomics, transcriptional regulation, or the analysis of large-scale sequencing datasets, particularly MPRA or population genetics data
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external) is reimagining the experimental neuroscience pipeline with big data and AI at its core. A central goal of the project is to build a foundation model of the visual brain—a “digital twin” that
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 17 days ago
molecular epidemiology, genetics, or translational breast cancer research. The successful candidate will lead research efforts using rich molecular and epidemiologic data from the Carolina Breast Cancer Study
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biochemistry, and large-scale genetic screening in our research approach. Basic Qualifications: 1. A Ph.D. in a relevant field 2. Demonstrated record of research achievement. 3. Strong written and oral