Scientist I, Computational Discovery

The Scientist, Cancer Genomics position sits within the Research & Early Development team in the Product Development group and is responsible for working on discovery projects to establish correlations between genotype and phenotype. Using a variety of phenotypic measures, the role supports the discovery of novel biomarkers, drug sensitivity, resistance signatures, and genomic alterations involved in tumorigenesis. The primary functions rely on leveraging FoundationCORE, FMI's 300,000+ tumor sample dataset, to investigate novel cancer gene alterations (including annotation using publicly-available online resources such as UniProt and The Cancer Genome Atlas Program) and prepare scientific manuscripts. Key Responsibilities Develop and evaluate potential biomarkers using FoundationCORE. Determine when statistical analysis is needed and apply the analysis. Use a computer cluster to analyze genomic signatures on historical samples. Communicate with Biopharma partners and internal departments as needed to define specifics of cancer mutations and other related scientific queries. Perform queries for Biopharma partners and return results. Utilize cancer genomics expertise to investigate genomic mechanisms of oncogenesis. Integrate appropriate clinical data with Next-Generation Sequencing (NGS) output. Work collaboratively with internal colleagues to refine analysis algorithms and methods. Contribute scientific expertise to broader projects within the Research and Development team. Other duties as assigned. Qualifications: Basic Qualifications: Bachelor's degree in related field and 3+ years of research experience preferred in the life sciences industry; OR, Master's and 2+ research experience preferred in the life sciences industry; OR, PhD and no experience Preferred Qualifications: 1+ years of industry or post-doctorate experience within Cancer Biology, Bioinformatics, Biochemistry, or another related life science 1+ years of industry or post-doctorate research experience with cancer genomics and/or next-generation sequencing principles Familiarity with one or more of the following scientific computing languages: Python, R, Matlab, or Java Familiarity with clinical nomenclature including stage, grade, ECOG, and the patient journey in oncology Familiarity with basic statistics Experience working with publicly available datasets, such as TCGA Ability to analyze and critically interpret scientific literature Effective oral and written communication skill Excellent writing skills and the desire to contribute to scientific manuscripts and abstracts Reliability, high ethical standards and integrity Translational research experience Understanding of HIPAA and importance of privacy of patient data Commitment to FMI values: patients, innovation, collaboration, and passion #LI-Hybrid