Computational Scientist I (Single-cell/Spatial Cancer Genomics)

Location: Onsite at the National Cancer Institute Shady Grove campus, 9609 Medical Center Dr, Rockville, MD 20850, USA

Salary: $103,100–$147,767 per year

Company

hirify.global, operated by Leidos Biomedical Research, conducts biomedical and cancer research in collaboration with the National Cancer Institute.

What you will do

• Lead end-to-end analyses of single-cell, multi-omics, spatial transcriptomics, and proteomics projects with multidisciplinary research teams.
• Design experiments, formulate hypotheses, develop analytical plans, and interpret cancer genomics findings.
• Implement and benchmark methods for sequencing- and imaging-based spatial omics, including segmentation, quality control, clustering, integration, and cell annotation.
• Study tumor microenvironments and immune cell infiltration through integrated multi-modal analyses.
• Develop reproducible workflows and scalable pipelines using containers, workflow management systems, version control, HPC clusters, and cloud environments.
• Communicate results through visualizations, reports, presentations, and manuscript contributions.

Requirements

• PhD in Bioinformatics, Computational Biology, Biostatistics, or a related field; foreign degrees require evaluation for U.S. equivalency.
• Demonstrated experience analyzing single-cell, single-nucleus multiomic, and spatial omics data from sequencing- and imaging-based platforms.
• Strong programming skills in R and Python, plus proficiency with Bash, AWK, SED, Linux, HPC, cloud environments, and Slurm.
• Experience with reproducibility and version control using Docker, Singularity, GitHub, Snakemake or Nextflow, Conda, R environments, and Markdown.
• Ability to work independently and collaboratively, communicate technical findings clearly, manage large datasets, and contribute to scientific publications.
• Ability to obtain and maintain a security clearance.

Nice to have

• At least three years of postdoctoral or equivalent academic or industry experience.
• Experience with platforms and tools including 10x Visium HD, Xenium, Ultivue, Cell Ranger, Space Ranger, StarDist, QuPath, Seurat, Scanpy, SpatialData, and Squidpy.
• Knowledge of batch correction, clustering, label transfer, cell-cell communication, differential expression, pathway enrichment, and spatial analysis methods.
• Public code portfolio demonstrating relevant single-cell or spatial omics expertise.
• Experience with bulk transcriptomics, proteomics, metabolomics, or other cancer genomics data.

Culture & Benefits

• Collaborative, multidisciplinary research environment supporting cancer genomics and prevention research.
• Opportunities for scientific co-authorship and collaboration with investigators and scientists.
• Health and wellness programs, income protection, paid leave, and retirement benefits.
• Work focused on reproducible, high-impact biomedical research and scientific discovery.