Postdoctoral Fellow - Diabetes, Inflammation, Hard and Soft Tissue Healing

Postdoctoral Fellow - Diabetes, Inflammation, Hard and Soft Tissue Healing


Location: University of Pennsylvania - School of Dental Medicine
Open Date: Feb 24, 2026
Deadline:

Faculty Mentor: Dana Graves, DDS DMSc

Department: Periodontics

Funding Source: Grant Funded

Number of Positions: 1

Open to applications from U.S. Citizens and foreign nationals

We are seeking an energetic Postdoctoral Fellow to join a fast-paced, highly collaborative laboratory investigating how diabetes reshapes immune regulation, cellular signaling, and hard and soft tissue healing. This role is designed for a hands-on, intellectually curious scientist who wants to take ownership of impactful projects while accelerating career growth through publication-driven science, mentorship, and leadership opportunities. You will work closely with faculty and trainees in a supportive, high-productivity environment with clear opportunities to build a strong track record in manuscripts, grant writing, conference presentations, and translational experimental design, positioning you competitively for the next step in academia, clinical and translational research, or industry. Strong communication skills, reliability, attention to detail, and enthusiasm for learning are essential

In this position, you will drive projects from concept to completion by contributing to experimental design, protocol development and optimization, execution, troubleshooting, and data interpretation across integrated in vivo and in vitro platforms. Experimental work will include translational studies in genetically modified mouse models, in vivo inhibitor approaches, and immune and tissue phenotyping to define how diabetes alters inflammation and repair, including mechanistic studies of wound healing involving soft tissue or bone, innate and adaptive immune responses and key immune-cell interactions such as dendritic cells and lymphocytes. You will apply a core toolkit spanning primary immune cell isolation and culture, functional immune assays, flow cytometry (panel design, staining optimization, acquisition, gating, and quantitative analysis), molecular and signaling assays (e.g., PCR and qPCR, pathway and protein readouts, reporter assays), and tissue-level analyses (histology, immunofluorescence or immunohistochemistry, and image-based quantification). A major emphasis of the role is cutting-edge transcriptomic research, including next-generation sequencing workflows such as bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics, with opportunities to integrate these datasets with mechanistic wet-lab findings. The successful candidate will contribute to bioinformatics and computational analysis, including quality control, alignment and quantification, differential expression, pathway and network enrichment, cell type annotation, trajectory and cell state analyses, and multi-modal integration across transcriptomics, flow cytometry, and tissue imaging. The fellow will actively contribute to manuscripts and grant applications through figure generation, methods and results drafting, data synthesis, and scientific storytelling, while also developing leadership skills through mentoring and supervision of lab members and presenting findings at internal seminars and national or international conferences as projects mature.


Qualifications
Eligibility for appointment as a postdoc requires candidates to hold, or to have completed the requirements fir an advanced degree e.g. PhD, MD or equivalent. Candidates from non U.S. universities must hold advanced degrees equivalent to thos awarded in the U.S. Institutions to qualify for appointment as postdoctoral fellow.


Application Instructions
Applicants must submit a CV, cover letter, and contact information for three professional references. All materials must be submitted through Interfolio.


To apply, visit https://apply.interfolio.com/182196

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), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.










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