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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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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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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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motivated Postdoctoral Research Fellow to develop and apply innovative, data-driven models for seismology, with a focus on developing cutting-edge foundation models. This is an exceptional opportunity
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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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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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). 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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on research pertinent to the project. By scaling up data, compute and model size, large language models (LLMs) have gained an impressive and ever growing array of capabilities. The next phase of development
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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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population-level outcomes. Utilize advanced quantitative methods to analyze large healthcare datasets, including Medicare and Medicaid claims (MedPAR, Outpatient, Carrier, TAF). Develop reproducible code and