The Laboratory of Pathology which is part of the Center for Cancer Research Division of the National Cancer Institute located in Bethesda, MD is seeking a post-doctoral fellow to conduct research in cancer genomics. As part of the NCI-COMPASS program the Laboratory of Pathology is developing a robust multiomics program which includes clinical-grade whole genome sequencing, whole transcriptome sequencing, and other genomic characterization modalities. We are generating a large amount of in-house NGS data (panel sequencing, RNAseq, whole genome sequencing) and are using state-of-the art approaches (synthetic lethality, genetic interactions) to translate these data into integrated genomic signatures and data-driven therapeutic options. The purpose of this effort is to detect accepted targets of therapy; targets relevant to clinical trial eligibility; undiscovered hereditary cancer predisposition biomarkers for individual patients; and biomarkers that can refine diagnoses. The data scientist will be central in formulating questions and analyzing the data produced by these platforms. An example of one approach would be incorporation of machine learning approaches to integrate pathology images with multiomic data and patient outcome to target therapies and immunotherapy. The individual accepted to this position will receive mentoring from both clinical and research-oriented pathologists including molecular pathologists and will have the opportunity to interact with leaders of genomic oncology at the NCI. Close collaboration with computational biologists in the Cancer Data Science Lab is expected to further enrich this experience.
Specific duties will include:
- Become up-to-date and maintain familiarity with current genomic oncology.
- Close collaboration with molecular pathologists and computational biologists to identify new approaches of data integration of multiplatform data.
- Ability to scrutinize in-house data and publicly available databases such as TCGA using standard computational packages (e.g. R, Python, etc) in order to answer complex questions.
- Produce scientifically relevant outputs based on specific analyses including graphical representations of data.
- Presenting relevant information in oral and written formats.
- Troubleshooting problems involving issues related to project design.
- Interacting with laboratory information system managers.