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Qualifications at this Level Education/Training: PhD (theoretical nuclear/high-energy physics, quantum information science, lattice gauge theories, quantum many-body dynamics) Experience: Preferred--computational
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, predictive modeling, machine learning, and causal inference methods. Experience with claims-based or EHR-based phenotyping, variable construction, treatment pattern analyses, healthcare utilization studies
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in AI for genomics (e.g., generative models, transformers, genomic language models, agentic AI) and related areas of statistics (e.g., uncertainty quantification for machine learning and AI). Apply
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to learn. Outstanding problem-solving skills. Must adhere to strict safety requirements. Ability to work and communicate effectively in a dynamic group environment. Other Requirements: This position is
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, longitudinal follow-up, biospecimen and clinical data collection, EHR-based cohort development, physiologic data integration, machine learning analysis, and manuscript and grant development. Minimum Requirements
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Postdoctoral Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates with non-US degrees may be required to provide proof of degree equivalency. 1. A candidate may also be appointed to a
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-edge technologies, including genetically engineered mouse models, patient-derived models, single-cell and spatial genomics, organoid systems, and preclinical therapeutic studies. Learn more about our
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manuscripts for publication in peer-reviewed journals. Prepare presentations for research conferences and prepare data for grant submission. Learn how to write fellowship grants. Train new personnel in the lab
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-heaton-phd/ Recent Ph.D. graduates (or people about to graduate) with interest in this topic are encouraged to apply. We value diversity of backgrounds and experience, so if you aren’t an expert in all