Bioinformatics Scientist I 631167 (NCI)
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POST DATE 8/28/2016
END DATE 1/7/2017
Leidos Biomedical Research, Inc.
JOB DESCRIPTIONLeidos Biomedical Research, Inc. (LBRI), a wholly owned subsidiary of Leidos, operates the Frederick National Laboratory for Cancer Research (FNLCR). FNLCR is a Federally Funded Research and Development Center (FFRDC) sponsored by the National Cancer Institute (NCI). It is the only FFRDC dedicated to biomedical research. Through its status as an FFRDC, FNLCR provides NCI and others with a unique national resource to accelerate the development and delivery of effective preventive, diagnostic, and therapeutic products for cancer and AIDS.
The breadth of FNLCR s activities spans the research and development spectrum, including investigator-initiated, hypothesis-driven research into cancer and AIDS; advanced technology programs focused on genetics and genomics, proteins and proteomics, imaging, nanotechnology, bioinformatics, and laboratory animal sciences; clinical operations in support of NCI and National Institute of Allergy and Infectious Diseases (NIAID)-sponsored clinical trials, as well as NCI drug discovery and development efforts; and management and operations of biopharmaceutical development and manufacturing programs under current Good Manufacturing Practice conditions for NCI and NIAID. Administrative, procurement, financial, safety, and facilities support is provided to these R&D activities through state-of-the-art business processes. LBRI has approximately 1,900 employees and manages an annual operating budget of approximately $450M.
For more information about Leidos Biomedical Research Inc., please visit our webpage at https://www.leidos.com/about/companies/leidos-biomedical-research.
The Cancer Genomics Research Laboratory (CGR) investigates the contribution of germline and somatic genetic variation to cancer susceptibility and outcomes in support of the NCI's Division of Cancer Epidemiology and Genetics (DCEG). Working in concert with epidemiologists, biostatisticians and basic research scientists in DCEG s intramural research program, CGR provides the capacity to conduct genome-wide discovery studies and targeted regional approaches to identify the heritable determinants of various forms of cancer.
The Cancer Genomics Research (CGR) laboratory in Gaithersburg, MD, is a fast-paced, high-throughput organization dedicated to the support of molecular, genetic and epidemiologic studies for investigators at the National Cancer Institute's Division of Cancer Epidemiology & Genetics (DCEG). The Division includes over 70 principal investigators in epidemiology, genetics, and biostatistics who conduct multidisciplinary family- and population-based research to discover the genetic and environmental determinants of cancer, and new approaches to cancer prevention. This includes the design and analysis of high throughput studies using various types of omics technologies such as array- and sequence-based genome-wide association studies, studies of tumor characteristics using integrated genomic data analysis and molecular epidemiologic studies based on novel metabolomic and microbiomic assays. We are seeking a highly motivated scientist to join the bioinformatics team at the CGR and provide analytical support to DCEG. Working with DCEG investigators, external collaborators, CGR management and staff, the Bioinformatics Scientist I will provide leadership and support to the extensive DCEG GWAS analytical efforts.
Duties include: 1) accessing, extracting and preparing data for analysis, including combining data run on multiple platforms as well as externally generated data in support of meta-analyses, 2) harmonizing and maintaining diverse data with associated metadata, 3) routine GWAS analytical tasks including data QC, imputation, population structure analysis, association analyses, 4) organizing results into clear presentations (including QQ-plots, Manhattan plots) and concise summaries of work, in formats useful for scientific interpretation, 5) development and execution of advanced analyses including multiplicative interaction analyses, pathway based analyses, integrative analyses and, 6) working closely with DCEG PIs in support of scientific manuscript development, submission, revision activities with significant coauthorship and potentially lead authorship opportunities