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The Kim Laboratory at the University of Utah is seeking a Postdoctoral Research Fellow to lead the biological arm of an NIH-funded cornea chip project. The role focuses on developing cell models and mechanobiology approaches at the interface of corneal biology and organ-on-chip engineering.
The ideal candidate has a PhD in a related field and a strong track record of first-author publications, with hands-on expertise in mammalian cell culture, CRISPR/Cas9 genome editing, and molecular imaging
The Kim Laboratory at the University of Utah (Department of Mechanical Engineering and John A. Moran Eye Center) is seeking a highly motivated, creative, and collaborative Postdoctoral Research Fellow. The fellow will lead the biological arm of an NIH-funded project on corneal mechanotransduction in keratoconus. This project sits at the intersection of corneal biology, mechanobiology, and organ-on-chip engineering, and builds on the laboratory's recent work on curvature-dependent regulation of corneal stromal cells (Nature Communications, 2025).
The successful candidate will generate and validate CRISPR/Cas9 knockout corneal stromal cell lines. They will also study how curvature and mechanical load regulate corneal cell behavior in hydraulically controlled organ-chip platforms, and identify the mechanotransduction pathways underlying keratoconus progression. Candidates should hold a Ph.D. in Cell Biology, Molecular Biology, Vision Science, Biomedical Engineering, or a related field, with a strong track record of first-author publications.
This role requires hands-on expertise in mammalian cell culture, CRISPR/Cas9 genome editing, and core molecular and imaging techniques such as qPCR, Western blotting, immunocytochemistry, and confocal microscopy. A solid understanding of mechanotransduction signaling, including YAP/TAZ, cytoskeletal remodeling, and ECM regulation, is essential. The preferred candidate will also bring experience with corneal or ocular cell culture, 3D or microfluidic culture systems, and RNA-seq or quantitative image analysis.