Computational Scientist; Position

Why RTI

RTI International is an independent, scientific research institute dedicated to improving the human condition. Our vision is to address the world's most critical problems with technical and science-based solutions in pursuit of a better future. Clients rely on us to answer questions that demand an objective and multidisciplinary approach—one that integrates expertise across social, statistical, data, and laboratory sciences, engineering, and other technical disciplines to solve the world’s most challenging problems.

We believe in the promise of science and technical solutions, and we push ourselves every day to deliver on that promise for the good of people, communities, and businesses in the US and around the world. If you are looking for the opportunity to make a real difference, RTI is the place for you.

RTI’s Genomics and Applied Public Health group is seeking a skilled and motivated Computational Scientist. The successful candidate will provide dedicated scientific and analytical support to the National Cancer Institute’s Division of Cancer Epidemiology & Genetics through their expertise in tumor genomics, lung cancer biology, and epidemiology. They will advance the Sherlock-Lung Study, a large-scale initiative investigating the genomic, transcriptomic, and methylation landscapes of lung cancer in never smokers, as well as their spatial architecture, to uncover mutational processes, molecular changes, and tumor evolution.

The successful candidate will lead integrative analyses and scientific interpretation of somatic high‑coverage whole‑genome sequencing (WGS) and multi‑omics datasets from the Sherlock‑Lung cohort, consisting of over 3,000 subjects. This position centers on hypothesis‑driven investigation that combines biological and computational expertise, with leadership in producing high‑impact publications that advance understanding of lung cancer development and progression.

This is a contract position anticipated to last up to one year, with the possibility of extension based on project needs and funding.

There is a strong preference for this position to be based onsite at the National Cancer Institute (NCI) Shady Grove campus in Rockville, MD.

• Formulate and test biological hypotheses related to mutational processes, intra‑tumor heterogeneity, clonal architecture, and evolutionary dynamics in lung cancer.
• Lead integrative analyses of somatic and germline variation (SNVs, indels, structural variants, copy number alterations), mutational signatures, and driver events using large‑scale short‑read and long‑read WGS and multi‑omics datasets.
• Apply advanced statistical approaches to extract insights from genomic datasets and synthesize findings with clinical and multi‑omics data.
• Critically evaluate and implement emerging analytical methods for single‑cell, spatial, and multi‑omics analyses to enhance biological discovery.
• Ensure analytical rigor, reproducibility, and scalability of computational workflows.
• Lead and contribute to peer‑reviewed publications, present findings at scientific meetings, and communicate results to multidisciplinary collaborators.
• Contribute to study design and analytic strategy for ongoing and future Sherlock‑Lung initiatives.

Minimum Qualifications:

• PhD degree and a minimum of two (2) years of progressively responsible relevant experience.
• Demonstrated experience and in‑depth understanding of tumor genomics and cancer biology.
• Proven expertise in next‑generation sequencing (NGS) data analysis and visualization using both custom and open‑source bioinformatics tools, with a focus on somatic whole‑genome sequencing analyses and multi‑omics data integration.
• Proficiency with core statistical methods and modern machine learning approaches appropriate for high‑dimensional genomic data, with emphasis on biological interpretability.
• Strong experience working with genomic databases such as TCGA, dbGaP, gnomAD, cBioPortal, ENCODE, 1000 Genomes, All of Us, GTEx, ICGC, PCAWG, and UK Biobank.
• Extensive proficiency in scripting and programming languages including Bash, R, and Python, with experience in RStudio, Jupyter…