Duke University
Top university
Just Landed
New Today
Postdoctoral Associate Duke University in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Available
Deadline
Apr 20, 2027
Country
United States
University
Duke University
Apply for this position
Keywords
Suggested positions
About this position
Postdoctoral Associate at Duke University supporting a recently funded project on kidney health in study cohorts from Sri Lanka.
The project has already completed its field-based work, and the biological specimens are now being transferred to Duke for laboratory processing and analysis. The postdoctoral researcher will work with human urine and blood samples, carrying out specimen preparation and molecular analyses that support biomarker discovery and validation in kidney injury and function.
This position is centered on multi-omics research at the intersection of kidney health, environmental exposures, and clinical phenotypes. The successful candidate will help analyze transcriptomic, proteomic, and metabolomic data, then integrate these molecular profiles with clinical and study data to identify biomarkers, molecular pathways, and biological signatures associated with kidney disease outcomes.
The role involves close collaboration with study investigators and multidisciplinary collaborators, with responsibilities spanning wet-lab specimen processing, computational analysis, reproducible workflows, and interpretation of results for reports, presentations, manuscripts, and grant deliverables. The work is based in Duke University’s NSOE-ENS & ECS department and is tied to a recently awarded grant with a one-year project timeline and possible extension.
Funding details
Available
What's required
Specialized expertise in kidney health and molecular analysis of human urine and blood specimens is required. Demonstrated expertise in transcriptomics, proteomics, and metabolomics is sought, along with experience analyzing high-dimensional omics datasets using normalization, quality control, differential expression or abundance analysis, multiple-testing correction, pathway and functional enrichment analysis, and biomarker discovery. Experience integrating transcriptomic, proteomic, metabolomic, and clinical/phenotypic data using computational and machine-learning approaches is particularly desirable, including supervised and unsupervised learning, dimensionality reduction, clustering, feature selection, predictive modeling, cross-validation, and multi-omics data integration.
How to apply
Apply through the Academic Jobs Online link provided in the advert. Submit your application materials via the application portal before the deadline.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.