Post-Doc Research Associate

For information on UNC Postdoctoral Benefits and Services

Our mission is to improve the health and well‑being of North Carolinians and others whom we serve. We accomplish this by providing leadership and excellence in the interrelated areas of patient care, education and research.

• Patient care:
  We promote health and provide superb clinical care while maintaining our strong tradition of reaching underserved populations and reducing health disparities across North Carolina and beyond.
• Education:
  
  We prepare tomorrow`s healthcare professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team‑oriented interprofessional education to ensure a highly skilled workforce.
• Research:
  We develop and support a rich array of outstanding health sciences research programs, centers and resources. We provide infrastructure and opportunities for collaboration among disciplines throughout and beyond our university to support outstanding research. We foster programs in the areas of basic, translational, mechanistic and population research.

The Brunk Lab at UNC
-Chapel Hill seeks a computational postdoctoral researcher to develop and apply methods for integrating single-cell sequencing and imaging data within controlled cell-line model systems. The project focuses on vertical integration of multimodal single-cell datasets, including single-cell DNA copy number, RNA expression, chromatin accessibility, protein abundance, protein localization, and cytogenetic imaging. The postdoctoral researcher will help build computational frameworks that connect sequencing-based measurements with imaging‑derived single-cell features, including multiplexed protein imaging and AI‑assisted cytogenetic image analysis.

This position is central to a funded research program developing single‑cell integration frameworks and AI imaging tools to understand how genome structure and molecular state coordinate across individual cells. The grant includes single‑cell multi‑omics sequencing, 4i protein imaging, CITE
-seq validation, and AI‑based cytogenetic analysis.

Ph.D. in computational biology, bioinformatics, biostatistics, computer science, genomics, systems biology, biomedical engineering, quantitative biology, or a related field.

• Strong programming skills in Python and/or R.
• Experience analyzing high‑dimensional biological data, especially single‑cell sequencing data.
• Strong statistical and quantitative reasoning skills.
• Ability to work independently and collaboratively in an interdisciplinary environment.
• Excellent written and oral communication skills.

• Experience with one or more of the following areas is strongly preferred:
• Single‑cell RNA
  -seq, single‑cell ATAC
  -seq, CITE
  -seq, single‑cell DNA copy number, or multi‑omics integration.
• Computational analysis of microscopy, multiplexed immunofluorescence, spatial/protein imaging, or image‑derived single‑cell phenotypes.
• Machine learning, latent variable modeling, variational autoencoders, optimal transport, graph‑based integration, or related computational approaches.
• Experience with tools such as Seurat, Scanpy, scVI, ArchR, Signac, Cell Ranger, Cell Ranger ARC , Harmony, LIGER , MOFA , or related packages.
• Experience with image‑analysis tools or libraries such as Cell Profiler, napari, ImageJ/Fiji, scikit‑image, Cellpose, PyTorch, Tensor Flow, or similar.

The University is an equal opportunity employer and welcomes all to apply without regard to age, color, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, or sexual orientation. We encourage all qualified applicants to apply, including protected veterans and individuals with disabilities.

Required Documents

• Curriculum Vitae / Resume

Optional Documents

• Cover Letter
• List of References

Required fields are indicated with an asterisk (*).