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encoded Ca²⁺ indicators, electrophysiology, molecular biology, optogenetics/chemogenetics, and transgenic mouse models to understand how cellular signaling networks coordinate normal gut motility and
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regulatory decision-making around the implementation of these technologies. A key component of the work will involve developing an ex-ante economic model to identify cost-effective strategies for implementing
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initial problem specification, data gathering and analysis, model creation, and implementation Strong understanding of artificial intelligence applications and methodologies, such as working knowledge
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
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molecular approaches, genetically modified animal models, advanced confocal imaging, flow cytometry, innovative culture models such as organoids, and working with clinical samples. The main responsibility
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data analysis (e.g., MRI preprocessing, statistical modeling, familiarity with tools such as FSL, SPM, AFNI, or similar platforms). Proficiency in statistical programming (e.g., R, Python, MATLAB
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-year appointments. Salary and benefits are competitive and commensurate with experience, following Princeton University guidelines. Research Scope Benchmarking and evaluating existing foundation models
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, including the PBWT/GBWT family of haplotype algorithms for biobank-scale identity-by-descent (IBD) detection, the Med-BERT and CovRNN clinical foundation models for electronic health records, and the UDIP
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: 1147547 Position Summary The Biomechanics Lab in the Department of Mechanical Engineering at Michigan State University is recruiting a Postdoctoral Research Associate to work on computational modeling
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science and engineering applied to stakeholder-relevant issues. The scientists will collaborate with Princeton and NOAA/GFDL researchers to expand the reach of GFDL's model data (both historical and future