Job Details

Postdoctoral Fellow in Single-Cell and Spatial Genomics Bioinformatics

Position Number: 9751404
Location: Philadelphia, United States
Position Type: Laboratory and Research

Postdoctoral Fellow in Single-Cell and Spatial Genomics Bioinformatics

Location: University of Pennsylvania, Penn Dental Medicine
Open Date: Aug 06, 2026
Deadline:

A postdoctoral position is available in the laboratory of Dr. Dana T. Graves at the University of Pennsylvania. The fellow will study inflammatory processes and how they impact the skin, mucosa, skeleton and periodontium in the context of diabetes, aging or other pathologic conditions. We seek a scientist who will lead computational analysis of single-cell, spatial, and multiomic datasets. The fellow will work closely with investigators who conduct complementary experimental studies. This is an opportunity to take substantial intellectual ownership of a disease-focused computational research program. The goal is to identify mechanisms of disease and potential therapeutic targets.

Research Focus

Our research examines how diabetes changes cell signaling, differentiation, immune-stromal interactions, and tissue repair. Projects span several tissues, disease models, species, and experimental platforms. The fellow will identify disease-associated cell states and transcriptional programs. The work will also address spatial signaling networks, cell-cell communication, and changes in cell state over time. Projects may include regulatory network inference, pseudotime analysis, and machine-learning approaches when these methods are scientifically appropriate.

Key Responsibilities

Lead analysis of single-cell RNA-seq and spatial transcriptomic data.

Develop clear, reproducible computational workflows.

Perform quality control, data integration, cell annotation, and differential expression analysis.

Conduct pathway, trajectory, state-transition, and ligand-receptor analyses.

Integrate multiomic, cross-species, and cross-cohort datasets.

Integrate transcriptomic data with imaging, histologic, and phenotypic measurements.

Create clear figures and communicate results to computational and experimental collaborators.

Help define analytical strategy and interpret biological findings.

Present results and prepare first-author manuscripts.

Contribute to grant development and collaborative studies.

A major focus will be analysis of 10x Genomics Xenium spatial transcriptomic and single-cell RNA-seq datasets. The primary environment uses R, Seurat, and related tools. The fellow may use other validated methods when they improve the analysis.

The Graves laboratory combines computational discovery with in vivo models, human specimens, histology, flow cytometry, immunofluorescence, and in vitro validation. Relevant experimental systems include genetically engineered mouse models, diabetic and aging models, primary mouse and human cell cultures, and molecular perturbation studies. The fellow will have substantial intellectual ownership of the project. This includes selecting analytical approaches, leading data analysis, presenting findings, and writing first-author papers. Dr. Graves will provide direct scientific mentoring and regular project guidance. The fellow will also work with collaborators and shared-resource specialists across the University of Pennsylvania. Penn core facilities provide support in single-cell and spatial genomics, biostatistics, imaging, histology, and quantitative analysis. The position offers training at the interface of computational biology, genomics, diabetes, inflammation, tissue repair, mouse genetics, and translational research. The goal is to support scientific independence, strong publications, grant development, and preparation for an academic or industry career.

Qualifications
A PhD, MD, DMD, DVM, or equivalent doctoral degree in a relevant field.

Hands-on experience with bioinformatic analysis of single-cell RNA-seq or spatial transcriptomic data.

Strong skills in R and modern single-cell analysis workflows.

Ability to interpret results in a biological and disease context.

Ability to work independently and collaborate across disciplines.

Clear scientific writing and communication skills.

Relevant fields include bioinformatics, computational biology, genomics, biostatistics, systems biology, molecular or cell biology, immunology, bioengineering, diabetes biology, skeletal biology, computer science, statistics, data science, or a related discipline.

Preferred Qualifications Include Experience in the Following Areas:

Spatial transcriptomics.

Seurat and related R packages.

Multiomic, multi-species, or cross-cohort integration.

Trajectory or pseudotime analysis, cell-cell communication analysis, or regulatory network inference.

Image analysis.

In vitro or in vivo validation experiments.

Integrating molecular data with imaging data.

Application Instructions
Start date: Available immediately following interviews and reference review.

Application materials: Submit a curriculum vitae, a brief statement describing research experience and future interests, and the names and contact information of three references.

Contact: Jen East, jeneast@upenn.edu

To apply, visit https://apply.interfolio.com/190925

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.