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developing study designs, programming experiments, data collection and analysis, manuscript preparation, research presentations, IRB submissions, and the supervision of students and research assistants
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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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, a current CV, and contact information for three references. Questions can be directed to Daniel Schmitt (daniel.schmitt@duke.edu). Applications will be evaluated by a search committee, with final
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information, national origin, race, religion, (including pregnancy and pregnancy related conditions), sexual orientation, or military status. Duke aspires to create a community built on collaboration
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committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion
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interventions and “nudges” in collaboration with external partners (e.g., companies, nonprofits, policy organizations) • Using advanced data analysis methods to extract interpretable patterns from large, messy
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into clinically efficacious therapies in patients. Maintain accurate laboratory documentation of experiments, including raw experimental data and laboratory notebooks. Monitor progress of research projects and
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sites; (20%) • Conduct analytical work at Duke labs to analyze the chemical and isotopic compositions, of rocks, waste rocks, tailings, groundwater, surface waters; (30%) • Evaluate data, write
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Program, and the field site in Kenya, and engage with investigators at all sites across various disciplines. The project will focus on conceptualizing, innovating, and implementing data-driven approaches
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, interdisciplinary collaboration, and group dynamics. Preference will be given to applicants with expertise in field experiments, survey methods, or quantitative data analysis. The postdoc will contribute to a new