Research Associate: T Cell Immunology & Multi-Omics

University of Pennsylvania Perelman School of Medicine; Philadelphia (Philadelphia County); On-site; USD 65,000 - 90,000; Full time

Job summary

The Division of Rheumatology at the Perelman School of Medicine, University of Pennsylvania, seeks a Research Associate to join Academic Support Staff. The appointment is initially one year, extendable to a maximum of three years based on performance and funding. Ph.D.

required with deep expertise in T cell biology and bioinformatics. Ideal candidates bring tissue culture and flow cytometry experience and a track record in bulk and single-cell RNA-seq, TCR-seq, and BCR-seq data analysis using R

Qualifications

• Ph.D. required with strong publication record.
• Expertise in T cell biology and bioinformatics.
• Experience with bulk and single-cell RNA-seq, TCR-seq, and BCR-seq data analysis.
• Ability to work independently and in collaborative settings.
• Strong problem-solving, communication, and organizational skills.

Responsibilities

• Perform T cell stimulation, antibody staining, and cell sorting.
• Prepare bulk and single-cell sequencing libraries.
• Analyze and integrate RNA-seq, ATAC-seq, TCR-seq, and BCR-seq data using R or Python.
• Apply advanced statistical modeling; familiarity with spatial transcriptomics a plus.
• Contribute to publication-driven projects on immune dysregulation and biomarkers for autoimmune diseases (e.g., T1D).

Skills

T cell biology

Bioinformatics

Statistical modeling

Computational methods

Education

Ph.D. degree

Tools

R

Python

Flow cytometry

Job description

The Division of Rheumatology at the Perelman School of Medicine, University of Pennsylvania, seeks a Research Associate to join Academic Support Staff. The appointment is initially one year, extendable to a maximum of three years based on performance and funding. Ph.D.

required with deep expertise in T cell biology and bioinformatics. Ideal candidates bring tissue culture and flow cytometry experience and a track record in bulk and single-cell RNA-seq, TCR-seq, and BCR-seq data analysis using R