Post-Doc Research Associate

University of North Carolina at Chapel Hill; Chapel Hill (NC); On-site; USD 55,000 - 75,000; Full time

Job summary

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.

Qualifications

• Ph.D. in a quantitative field related to biology, computation, or statistics.
• Strong programming in Python and/or R with substantial data experience.
• Experience analyzing single-cell or high‑dimensional biological data.
• Excellent written and oral communication skills.

Responsibilities

• Develop computational frameworks for integrating multimodal single-cell data.
• Connect sequencing measurements with imaging‑derived features in models.
• Collaborate across interdisciplinary teams to validate methods.
• Contribute to AI imaging tools and cytogenetic analysis workflows.

Skills

Python

R

high‑dimensional data analysis

statistical reasoning

independent & collaborative work

communication skills

Education

Ph.D. in computational biology / bioinformatics / related field

Tools

Seurat

Scanpy

scVI

ArchR

Signac

Cell Ranger

Harmony

LIGER

MOFA

CellProfiler

napari

ImageJ/Fiji

scikit-image

PyTorch

TensorFlow

Job description

For information on UNC Postdoctoral Benefits and Services

Primary Purpose of Organizational Unit

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.

Position Summary

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.

Minimum Education and Experience Requirements

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

Required Qualifications, Competencies, and Experience

• 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.

Preferred Qualifications, Competencies, and Experience

• 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 CellProfiler, napari, ImageJ/Fiji, scikit‑image, Cellpose, PyTorch, TensorFlow, or similar.

Equal Opportunity Employer Statement

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.

Optional and Required Documents

Required Documents

• Curriculum Vitae / Resume

Optional Documents

• Cover Letter
• List of References

Supplemental Questions

Required fields are indicated with an asterisk (*).