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experience in life cycle assessment (LCA) and related tools for managing large data sets to evaluate natural resources needed to advance emerging technologies. The candidate will lead their primary project and
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mathematics and engineering. The Interpretable Machine Learning Lab has dedicated access to high-performance CPU and GPU computing resources provided by Duke University’s Research Computing unit and state
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-funded Duke lab hub for the Human Health Exposure Analysis Resource ) program, the Newborn Epigenetics STudy (NEST) longitudinal birth cohort, the Children’s Health and Discovery Initiative (CHDI
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support to early-career scientists pursuing research in benign urology. Eligible candidates will have access to KURe program resources to enhance their trajectory toward research independence. The Ur-BIOME
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or natural resource economics, ecological economics, or a related field. • Background in environmental modeling, programming, and LCA tools • Demonstrated ability to work collaboratively on cross-disciplinary
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for a postdoctoral research position at Duke University in topic area of environmental geochemistry. The Postdoctoral Associate will lead a project on critical metals resourcing in mine wastes
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interactions and to utilize bioinformatics resources an d high-dimensional –omics data to elucidate the biological significance of the statisticalanalysis. The postdoctoral fellow, under the mentorship of Dr
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statistical models to investigate gene by environment interactions and to utilize bioinformatics resources and high-dimensional –omics data to elucidate the biological significance of the statistical analysis
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, software engineering, and the life sciences. The group has access to Duke’s TEM facility and dedicated computational resources that are supported and maintained by Duke University's Research Computing unit