PROGRAM DESCRIPTION The Frederick National Laboratory is dedicated to improving human health through the discovery and innovation in the biomedical sciences, focusing on cancer, AIDS and emerging infectious diseases. The Biomedical Informatics and Data Science (BIDS) directorate works collaboratively and helps to fulfill the mission of Frederick National Laboratory in the areas of biomedical informatics and data science by developing and applying world leading data science and computing technologies to basic and applied biomedical research challenges, supporting critical operations, developing and delivering national data resources, and employing leading-edge software and data science to effectively enable and advance science. The Advanced Biomedical and Computational Science (ABCS) group is a part of BIDS within Leidos Biomedical Research as a technological hub of translational scientists with expertise in structural biology, biology, chemistry, imaging, and informatics. ABCS develops state-of-the-art technologies in large-scale data modeling, analysis, and integration and supports the scientific research at the Frederick National Lab by helping translate scientific questions to technical solutions for cancer and biomedical research. The Data Solutions and Systems Biology (DSSB) group in ABCS strives to streamline and provide innovative solutions for the NCI/NIH community to access and use biological information collected across different sources and formats. Integrating diverse data sources to streamline project requests and analysis workflows, enable disease agnostic access and analysis, variant impact annotation, identifier conversions across species, and merging clinical and research data enabling translation from basic to the goal of precision medicine. KEY ROLES/RESPONSIBILITIES Review existing literature and data sources on rare disease research Develop analytics approaches to understand correlations and patterns in rare disease genomics and therapeutics Work with the team to build use cases and prioritize data analytics tasks Document approaches and processes clearly and comprehensively BASIC QUALIFICATIONS To be considered for this position, you must minimally meet the knowledge, skills, and abilities listed below: Possession of Bachelor's degree from an accredited college/university according to the Council for Higher Education Accreditation (CHEA) in computer science, Math or Biomedical Science or a related field or four (4) years relevant experience in lieu of degree. Foreign degrees must be evaluated for US equivalency In addition to the education requirement, 0-2 years of progressively responsible experience Demonstrated ability to understand and develop machine learning algorithms in the bioinformatics field Expertise in R and/or Python Knowledge in scripting languages and Unix/Linux OS scripting Knowledge of genomics, chemoinformatics and multi-omic data integration Ability to self-direct with little or abstract day-to-day instruction Excellent written and verbal communication skills/ability to document and communicate complex scientific concepts for a variety of audiences Ability to obtain and maintain a security clearance PREFERRED QUALIFICATIONS Candidates with these desired skills will be given preferential consideration: Experience in clinical and genomics research Experience with web and database technologies Experience with high-performance computing A minimum of two (2) years of experience in a related field