Description
Postdoctoral Fellow: Extracellular Matrix Remodeling of the Pelvic Floor - Florian-Rodriguez Lab
The Department of Obstetrics and Gynecology and the Cecil H. and Ida Green Center for Reproductive Biology Sciences has a postdoctoral training position available in the Florian-Rodriguez Lab. The lab's research focuses on defining the cellular and molecular mechanisms underlying pelvic organ prolapse (POP), with particular emphasis on cellular senescence, extracellular matrix (ECM) remodeling, and tissue biomechanics that contribute to pelvic floor dysfunction. The Florian-Rodriguez Lab employs an interdisciplinary approach integrating animal models, molecular and cellular biology, histology, tissue biomechanics, and multi-omic data analysis. Ongoing projects aim to identify cellular drivers of ECM disruption and senescence in pelvic tissues and to discover novel biomarkers and therapeutic targets for POP and related pelvic floor disorders. The lab is particularly interested in leveraging transcriptomic and computational approaches to complement experimental studies. The postdoctoral fellow will design and lead independent research projects under the mentorship of the Principal Investigator, applying experimental and/or computational approaches to study pelvic floor biology. Responsibilities include the analysis and interpretation of high-dimensional datasets, such as transcriptomic or other omics data, using bioinformatics and computational methods as appropriate. The fellow will integrate molecular, cellular, and computational findings to address translational research questions, contribute to manuscript preparation, present research findings at scientific meetings, and actively participate in collaborative, multidisciplinary research efforts.
Qualifications
Applicants must hold a Ph.D. and/or M.D. in a relevant discipline, including but not limited to molecular biology, cell biology, reproductive biology, bioengineering, bioinformatics, or computational biology. Candidates should demonstrate a strong publication record reflecting scientific rigor and productivity. Experience in bioinformatics, computational biology, transcriptomic data analysis, or multi-omic integration is highly desirable, as is experience with molecular biology techniques, animal models, histology, or biomechanics. Successful candidates will have a demonstrated ability to work independently, think critically, and collaborate effectively within a multidisciplinary research environment.
Application Instructions
Interested candidates should submit a curriculum vitae (PDF), a brief statement describing research interests and career goals, and contact information for three (3) professional references.