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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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hyperparameter optimization and experiment tracking. Collaborate with research teams to implement robust validation strategies and statistical methodologies. Model Evaluation & Validation Evaluate model
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modeling and analysis. Ability to select, implement, diagnose, and adapt parameter-estimation or statistical-inference methods to suit the model, data structure, and scientific question. Experience with
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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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, physiology, eye-tracking, or related wearable measurements. ● Strong statistical analysis skills. ● Strong programming skills in a programming language used for data manipulation and statistical analysis
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/or quantitative methods expertise. Experience with implementation science. Experience using statistical or qualitative software. Other Requirements: Full-time, one-year fellowship (renewable based
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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