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outside of Duke University on cancer-focused research projects that aim to improve the understanding of clinical outcomes and advance statistical methodology. You will contribute to projects focused
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(45%) • Support statistical analyses of large data sets from an epidemiological cohort, investigating associations with birth outcomes using both targeted and nontargeted data (25%) • Support
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) Evaluate the implications of these associations for extraction processes; and 3) Assess the critical mineral resource potential of unconventional wastes through geospatial and statistical analysis of supply
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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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apply advanced computational and statistical analysis methods to quantify neural signaling dynamics associated with motor learning. Collaborate with faculty, trainees, and research staff to advance
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and deliverables. Learn background/research methods of studies for which analysis is conducted with limited direction and supervision. Statistical analysis and database management. Conduct systematic
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: Experience with mathematical, computational, or statistical modeling Experience developing simulation models, agent-based models, network models, stochastic systems, or dynamical systems Experience with R
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updates, SOP development, and other research operations as needed. · Participating in laboratory meetings and study team meetings. · Contributing to data summaries, basic statistical analyses, abstracts
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Position Description The Signal Inference, Information and Learning (SIIL) Group is seeking a Postdoctoral Researcher to perform research in the area of statistical signal and array processing with
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doctoral degree in Epidemiology, Biostatistics, or a closely related quantitative field Demonstrate strong computational and statistical training, including experience with complex data analysis Have