University of North Carolina at Chapel Hill
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Postdoctoral Research Associate in Single-Cell Multi-Omics Integration and AI Imaging at University of North Carolina at Chapel Hill University of North Carolina at Chapel Hill in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Funded postdoctoral research program at UNC-Chapel Hill. The posting lists a hiring range of $47,476 - $63,480 and notes UNC postdocs receive comprehensive medical and vision coverage, paid leave, and professional development benefits. The project is supported by a grant including single-cell multi-omics sequencing, 4i protein imaging, CITE-seq validation, and AI-based cytogenetic analysis.
Country
United States
University
University of North Carolina at Chapel Hill

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About this position
University of North Carolina at Chapel Hill is recruiting a Post-Doc Research Associate in the Brunk Lab within the Department of Biological and Genome Sciences.
This postdoctoral position focuses on computational biology, bioinformatics, genomics, single-cell multi-omics, machine learning, and AI imaging. The project aims to develop and apply methods for integrating single-cell sequencing and imaging data in controlled cell-line model systems. Research topics include vertical integration of multimodal single-cell datasets such as single-cell DNA copy number, RNA expression, chromatin accessibility, protein abundance, protein localization, and cytogenetic imaging.
The successful candidate 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. The grant supports single-cell multi-omics sequencing, 4i protein imaging, CITE-seq validation, and AI-based cytogenetic analysis.
Applicants must hold a Ph.D. in computational biology, bioinformatics, biostatistics, computer science, genomics, systems biology, biomedical engineering, quantitative biology, or a related field. Required skills include strong programming in Python and/or R, experience with high-dimensional biological data analysis, especially single-cell sequencing data, strong statistical and quantitative reasoning, and the ability to work independently and collaboratively. Excellent written and oral communication skills are also required.
Preferred experience includes single-cell RNA-seq, single-cell ATAC-seq, CITE-seq, single-cell DNA copy number, multi-omics integration, microscopy or multiplexed immunofluorescence, spatial/protein imaging, image-derived single-cell phenotypes, and computational methods such as latent variable modeling, variational autoencoders, optimal transport, and graph-based integration. Familiarity with tools such as Seurat, Scanpy, scVI, ArchR, Signac, Cell Ranger, Harmony, LIGER, MOFA, CellProfiler, napari, ImageJ/Fiji, scikit-image, Cellpose, PyTorch, or TensorFlow is preferred.
Location: Chapel Hill, North Carolina, United States. The position is full-time temporary for 12 months, with a hiring range of $47,476 to $63,480 and benefits including medical and vision coverage and paid leave.
Apply via the UNC PeopleAdmin portal. The posting is open until filled.
Funding details
Funded postdoctoral research program at UNC-Chapel Hill. The posting lists a hiring range of $47,476 - $63,480 and notes UNC postdocs receive comprehensive medical and vision coverage, paid leave, and professional development benefits. The project is supported by a grant including single-cell multi-omics sequencing, 4i protein imaging, CITE-seq validation, and AI-based cytogenetic analysis.
What's required
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 are required, along with experience analyzing high-dimensional biological data, especially single-cell sequencing data. Applicants should have strong statistical and quantitative reasoning skills, be able to work independently and collaboratively, and have excellent written and oral communication skills. Preferred experience includes single-cell RNA-seq, single-cell ATAC-seq, CITE-seq, single-cell DNA copy number, multi-omics integration, microscopy or multiplexed immunofluorescence analysis, machine learning, latent variable modeling, variational autoencoders, optimal transport, graph-based integration, and tools such as Seurat, Scanpy, scVI, ArchR, Signac, Cell Ranger, Harmony, LIGER, MOFA, CellProfiler, napari, ImageJ/Fiji, scikit-image, Cellpose, PyTorch, or TensorFlow.
How to apply
Apply through the UNC PeopleAdmin posting using the application link. Review the posting details and submit the required materials via the university portal. For questions about the application process, contact the Office of Postdoctoral Affairs.
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