The Basic Science Program (BSP) pursues independent, multidisciplinary research in basic and applied molecular biology, immunology, retrovirology, cancer biology, and human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick National Laboratory for Cancer Research (FNLCR). The Cancer & Inflammation Program (CIP), Basic Science Program, HLA Immunogenetics Section, under the leadership of Dr. Mary Carrington, studies the influence of human leukocyte antigens (HLA) and specific KIR/HLA genotypes on risk of and outcomes to infection, cancer, autoimmune disease, and maternal-fetal disease. Recent studies have focused on the impact of HLA gene expression in disease, the molecular mechanism regulating expression levels, and the functional basis for the effect of differential expression on disease outcome. The lab's further focus is on the genetic basis for resistance/susceptibility to disease conferred by immunogenetic variation. KEY ROLES/RESPONSIBILITIES The Computational Scientist will provide research support to the CIP-BSP-HLA Immunogenetics Section by consulting on biostatistical aspects of genomics experimental design, processing next-generation sequencing data, analyzing genomic variation (including genotype imputation) and reporting of research projects conducted in the lab. This individual will be expected to be familiar with querying biological databases (especially repositories of publicly available genomic data) Experience in statistical modeling of genomics data is also desirable Develops computational tools for addressing a broad range of general bioinformatics questions Consults with colleagues and other scientists on problems of mutual interest Critically evaluates research findings as a basis for further investigations Collaborates with experimentalists on the development of models and the use of these models to test hypothesis Communicate effectively and proactively, orally and in writing, with technical and non-technical individuals both internal and external; exercise independent judgment in developing methods, techniques and evaluation criteria to obtain desired results; must be detail-oriented and possess strong organizational skills with the ability to prioritize tasks BASIC QUALIFICATIONS Possession of a Doctoral degree in a related field from an accredited college or university according to the Council for Higher Education Accreditation. (Additional qualifying experience may be substituted for the required education). Foreign degrees must be evaluated for US equivalency In addition to the educational requirements, a minimum of five (5) years of competent, innovative research in a field of specialty Broad familiarity with open-source software environments for processing/analyzing genomics data derived from next-generation sequencing (NGS) studies Proficiency in developing test or production methods or protocols Must be familiar with computational tools available for molecular modeling including a detailed knowledge of the use of commercial tools for structural analysis as well as the capability to develop novel computational tools or specific tasks. Familiarity with GATK or similar pipelines for variant calling from raw NGS data Extensive experience with statistical software, such as SAS, R or S-Plus Experience with statistical analysis of GWAS/WGS/WES variants (PLINK/MaCH/IMPUTE2 and similar) Experience with relational database management systems (eg mySQL, Microsoft SQL Server) Knowledge of at least one scripting language (Python or Perl preferred) Ability to contribute to the interpretation and publication of research results Must be able to obtain and maintain a security clearance PREFERRED QUALIFICATIONS Experience with creating advanced graphics in R Experience with database administration and maintenance Expected competencies: Analysis of Next Generation sequencing data Equal Opportunity Employer (EOE) | Minority/Female/Disabled/Veteran (M/F/D/V) | Drug Free Workplace (DFW)