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The University of Pennsylvania's Penn Dental Medicine invites applications for a Postdoctoral Fellow in Senescence, Aging and Inflammation. The project investigates how senescence and inflammatory signals affect aging-related periodontal pathology, using mouse models and human tissues.
The fellow will perform scRNA-seq and Xenium spatial genomics analyses, integrate data with imaging, and contribute to manuscripts and grant applications, with mentoring from Dr.
Location: University of Pennsylvania - Penn Dental Medicine
Open Date: Sep 18, 2026
A postdoctoral position is available in the laboratory of Dr. DanaT. Graves at the University of Pennsylvania School of DentalMedicine, Department of Periodontics. The fellow will investigatemechanisms by which cellular senescence and inflammation intersectto alter age-associated pathogenesis. The position integratesexperimental biology with single-cell RNA sequencing (scRNA-seq),10x Genomics Xenium spatial transcriptomics, quantitative imaging,and molecular and cellular validation to define disease-associatedcell states, inflammatory signaling networks, and potentialtherapeutic targets.
The research program will examine how senescent cell states andinflammatory signals influence pathology that enhances aging-linkedpathology using a periodontal mouse model and human tissuevalidation. The fellow will participate in in vivo studies andanalyses of scRNA-seq and 10x Genomics Xenium datasets to identifysenescence-associated and inflammation-associated cell states,transcriptional programs, cell-cell communication networks,spatially organized cellular responses and mechanisms that lead togreater bone resorption. The analyses may include pathway analysis,trajectory and pseudotime analysis, regulatory-network inference,and ligand-receptor analysis. Experimental studies of aging andsenescence will include genetically engineered mouse models,primary mouse and human cell cultures, molecular perturbationstudies, histology, immunofluorescence, flow cytometry,quantitative image analysis, and other approaches used to validatecomputational findings and define mechanisms linking aging,senescence and inflammation with altered tissue function.
For single-cell and spatial genomics studies, the primarycomputational environment uses R, Seurat, and related tools, withother validated methods used when they improve analytical rigor orbiological interpretation. Quantitative imaging andspatial-analysis tools will be selected based on the specimens,imaging modalities, and scientific questions. Candidates withstrong experimental backgrounds will have opportunities to developadditional expertise in computational analysis, while candidateswith strong computational backgrounds will have opportunities togain experience with biological validation and experimentalsystems.
The Graves laboratory integrates computational discovery with invivo models, human specimens, histology, flow cytometry,immunofluorescence, primary cell culture, molecular perturbationstudies, and quantitative analysis. The fellow will havesubstantial intellectual ownership of their project, includingdevelopment of experimental directions, selection of analyticalapproaches, interpretation and presentation of findings,preparation of first-author manuscripts, and participation in grantwriting. Development of independent fellowship applications isencouraged.
Dr. Graves will provide direct scientific mentoring and regularproject guidance. The fellow will collaborate with investigatorsand shared-resource specialists across the University ofPennsylvania. Penn core facilities support single-cell and spatialgenomics, biostatistics, imaging, histology, and quantitativeanalysis. The position is designed to support scientificindependence, strong publications, grant development, andpreparation for an academic or industry career.
Equal Employment Opportunity Statement. The University of Pennsylvania is an equal opportunity employer.Candidates are considered for employment without regard to race,color, sex, sexual orientation, religion, creed, national origin(including shared ancestry or ethnic characteristics), citizenshipstatus, age, disability, veteran status or any class protectedunder applicable federal, state, or local law.