410 machine-learning-"https:" "https:" "https:" Postdoctoral positions in United States
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Field
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) Cleaning and managing large datasets from administrative data sources or online learning platforms Causal machine learning (e.g., double/debiased machine learning (DML), causal forests, generic ML) Learning
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to contribute to one or more projects, learning advanced cellular and molecular biology and anaerobic microbiology techniques. The candidate’s day will be split between benchwork to generate data, and computer
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multi-omic sequencing, network biology, and machine learning to identify actionable biomarkers and therapeutic vulnerabilities. The successful candidate will work at the interface of computational
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applications, and ability to quickly learn and master various computer programs. Must be technically rigorous, organized, and have demonstrated excellence, innovation, and productivity in research. Ability
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applications for a Postdoctoral Scholar, Instruction position for the Fall 2026 semester. The selected candidate will teach at the undergraduate level, including general chemistry, along with supervision
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Posting Summary Logo Posting Number RTF00052PO26 USC Market Title Post Doctoral Fellow Link to USC Market Title https://uscjobs.sc.edu/titles/156387 Business Title Post Doctoral Fellow Campus
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insurance, generous paid leave and retirement programs. To learn more about UofSC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Research Grant or Time
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other computer skills. Preferred Qualifications Prior experience in at least one of the following areas is highly desirable: (a) strong understanding of metabolism, such as the roles of lipid oxidation in
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: Experience applying machine learning methods for predictive analysis. Expereince with the Python programming language. Experience with the creation, validation, and use of synthetic data for constructing
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, Machine Learning, or a directly related field at the time of appointment is required. The successful applicants will be expected to have a strong statistical and computational background, research