Postdoctoral Fellow in Senescence, Aging and Inflammation

About the role

The Opportunity A postdoctoral position is available in the laboratory of Dr. Dana T. Graves at the University of Pennsylvania School of Dental Medicine, Department of Periodontics. The fellow will investigate mechanisms by which cellular senescence and inflammation intersect to alter age-associated pathogenesis. The position integrates experimental biology with single-cell RNA sequencing (scRNA-seq), 10x Genomics Xenium spatial transcriptomics, quantitative imaging, and molecular and cellular validation to define disease-associated cell states, inflammatory signaling networks, and potential therapeutic targets. The research program will examine how senescent cell states and inflammatory signals influence pathology that enhances aging-linked pathology using a periodontal mouse model and human tissue validation. The fellow will participate in in vivo studies and analyses of scRNA-seq and 10x Genomics Xenium datasets to identify senescence-associated and inflammation-associated cell states, transcriptional programs, cell-cell communication networks, spatially organized cellular responses and mechanisms that lead to greater bone resorption. The analyses may include pathway analysis, trajectory and pseudotime analysis, regulatory-network inference, and ligand-receptor analysis. Experimental studies of aging and senescence will include genetically engineered mouse models, primary mouse and human cell cultures, molecular perturbation studies, histology, immunofluorescence, flow cytometry, quantitative image analysis, and other approaches used to validate computational findings and define mechanisms linking aging, senescence and inflammation with altered tissue function.

Responsibilities

• Investigate molecular and cellular mechanisms linking senescence and inflammation to tissue dysfunction, repair, and regeneration using in vivo mouse models.
• Lead or contribute substantially to bioinformatic analyses of scRNA-seq and 10x Genomics Xenium spatial transcriptomic datasets.
• Develop and execute rigorous experimental approaches using in vivo, ex vivo, and/or in vitro models as appropriate to the project.
• Perform quality control, data integration, cell annotation, differential expression, pathway, trajectory, state-transition, and ligand-receptor analyses.
• Integrate transcriptomic findings with imaging, histologic, cellular, and phenotypic measurements.
• Use immunofluorescence and quantitative image analysis to characterize cellular localization, spatial distribution, and tissue organization.
• Develop rigorous, reproducible experimental and computational workflows.
• Interpret findings in biological and disease contexts and contribute to analytical and experimental strategy.
• Generate clear figures, present findings, and communicate effectively with computational and experimental collaborators.
• Prepare first-author manuscripts and contribute to grant development and collaborative studies.

Requirements

• A PhD, MD, DMD, DVM, or equivalent doctoral degree in a relevant field.
• A strong background in cell biology, molecular biology, immunology, skeletal biology, bioengineering, genomics, computational biology, bioinformatics, systems biology, or a related discipline.
• Demonstrated scientific rigor and the ability to interpret experimental or computational findings in a biological context.
• Ability to work independently and collaborate effectively across disciplines.
• Strong scientific writing, presentation, and communication skills.

Preferred Qualifications

• Experience with aging, cellular senescence, inflammation, immune biology, tissue repair, or related areas.
• Experience with mouse genetics and disease models, molecular and cellular assays, histology, immunofluorescence, flow cytometry, or quantitative image analysis.
• Experience with scRNA-seq or spatial transcriptomics.
• Experience integrating molecular, imaging, histologic, and phenotypic data.
• Candidates with a strong experimental background who wish to develop expertise in single-cell and spatial genomics, or computational candidates who wish to expand their experimental expertise, are encouraged to apply.