Job Summary We are seeking an MD-trained Postdoctoral Research Fellow for a two-year research fellowship focused on clinical and translational research in lipodystrophy. The fellow will work within the University of Michigan Lipodystrophy Program and LD-LYNC prospective natural history study, in close collaboration with investigators from ECLIP. The fellow has already established experience working across these collaborative datasets, including integration of LD-LYNC and ECLIP data to evaluate criteria for metabolic dysfunction-associated steatohepatitis (MASH) in individuals with lipodystrophy. Building on this foundation, the major goal of the fellowship will be to develop reproducible workflows for harmonizing and analyzing multidimensional clinical data across LD-LYNC and ECLIP and to use these resources to address important unresolved questions in lipodystrophy. Responsibilities* Develop and document reproducible workflows for harmonizing LD-LYNC and ECLIP variables, definitions, and longitudinal data. Create common data dictionaries and analytic definitions that can be used across participating cohorts. Identify areas in which existing diagnostic definitions or outcome measures are insufficient and develop testable approaches to improve them. Perform statistical analyses of cross-sectional and longitudinal clinical data in collaboration with biostatistical and bioinformatics colleagues. Participate in standardized collection, processing, tracking, and annotation of research biospecimens, including DNA and serum/plasma samples. Assist in linking biospecimen inventories with detailed clinical phenotype and longitudinal outcome data. Participate in exploratory biomarker analyses, including serum proteomic studies and other available multi-omic platforms. Perform pathway-level interpretation of biomarker data using tools such as Reactome and related pathway-enrichment approaches. Evaluate whether molecular signatures distinguish clinically important lipodystrophy phenotypes, including genetically defined and clinically defined subgroups. Explore biomarker signatures associated with liver disease, metabolic severity, treatment response, and patient-reported outcomes. Lead individual scientific projects arising from the integrated datasets and biospecimen resources. Coordinate closely with investigators at the University of Michigan, ECLIP, and collaborating international centers. Participate in development and implementation of PRO collection and analysis. Prepare abstracts, manuscripts, and presentations arising from the collaborative work. Contribute to development of future multicenter studies, prospective protocols, and grant applications. Maintain rigorous standards for data provenance, biospecimen tracking, reproducibility, regulatory compliance, and protection of participant data. Modes of Work Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes. U-M EEO Statement The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.