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, United States of America [map ] Subject Areas: Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Computer Science Machine Learning Appl Deadline: none (posted 2025/08
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regional leadership in biostatistics, genomics, biomedical informatics, artificial intelligence and health data science. The Postdoctoral Associate will conduct research in statistical machine learning and
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related field • Strong quantitative background (e.g. ecological theory and mathematical modeling, hierarchical statistical modeling, machine learning, remote sensing, geospatial statistics) • Demonstrated
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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell
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/bioinformatics, and data science. Work Performed · Work in highly collaborative inter-disciplinary environment with clinicians, econometricians, statisticians, and data scientists · Lead statistical analysis
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to climate, environment, or sustainability challenges. • Required skills: o Strong quantitative background, with expertise in one or more of the following: statistical modeling, machine learning, remote
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responses. Qualifications: A doctoral degree in a relevant field is required, preferably a quantitative field such as epidemiology, bioinformatics, statistics, computer science or engineering. The ideal
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in the United States. Preferred methodological skills include statistical analysis of survey and other large-n data, qualitative interviews, and/or text analysis and machine learning skills
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person with an interdisciplinary background and training. QUALIFICATIONS: REQUIRED: o Very strong statistical and analytical skills with a strong background in causal inference approaches (e.g
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presentation skills for engaging diverse stakeholders. Minimum Requirements: Requires a minimum of a PhD in disciplines such as epidemiology, health demography, bioinformatics, statistics, computer science