Bioinformatics Analyst II/III
Job ID: req1906
Employee Type: exempt full-time
Location: NIH Campus 9000 Rockville Pike, Bethesda, MD 20892 USA
The Frederick National Laboratory is a Federally Funded Research and Development Center (FFRDC) sponsored by the National Cancer Institute (NCI) and operated by Leidos Biomedical Research, Inc. The lab addresses some of the most urgent and intractable problems in the biomedical sciences in cancer and AIDS, drug development and first-in-human clinical trials, applications of nanotechnology in medicine, and rapid response to emerging threats of infectious diseases.
Accountability, Compassion, Collaboration, Dedication, Integrity and Versatility; it's the FNL way.
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.
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 Developmental Therapeutics Branch (DTB, Center for Cancer Research, NCI) advances novel therapeutic strategies and conducts clinical trials based on cancer-specific genomic, epigenetic, and metabolic alterations, drug design, molecular mechanisms of drug action to achieve precision medicine. The DTB is organized in several research groups lead by Principal Investigators focusing on complementary areas of interest. Dr. Anish Thomas (MBBS, M.D., NIH Lasker Clinical Research Scholar, Small Cell Lung Cancer Group) is a clinical researcher with a focus on small cell lung cancer, one of the most aggressive cancers. The goals of his research program are 1) to systematically develop more effective therapies for patients with SCLC and similar chemotherapy-refractory tumors by targeting key pathways involved in DNA replication, repair, and chromatin remodeling, and 2) genomic characterization of SCLC to understand the biology of treatment response and resistance, and to translate these findings into new treatment approaches.
- Provide collaborative bioinformatics support to the investigators at the Small Cell Lung Cancer Group, Development Therapeutics Branch, Center for Cancer Research, National Cancer
- Collect and review data; analyze and interpret data and results; provide reports based on analysis of scientific data, and report research outcomes to make recommendations for future work
- Develop and maintain Data Management pipelines for next-generation sequencing data generated in the SCLC clinical group (including but not limited to transcriptomics, proteomics, epigenetic data)
- Work in conjunction with the CCR Collaborative Bioinformatics Resource (CCBR) team to adopt best practices for analysis of various NGS data
- Work with staff on data visualization to support the preparation of presentations and manuscripts for submission to scientific journals
- Consult with members of the group to guide experimental design, carrying out primary/secondary data analysis on generated data
- Assist the group in submitting data to public genomic databases, such as GEO, dbGaP in compliance with the NIH Genomic Data Sharing Policy
- Train PostDocs and other staff to use NGS and other genomic analysis tools
- Develop other bioinformatic pipelines for processing genomic data such as ChIP-seq, DNAse-seq, single-cell sequencing, etc.
- Attend relevant branch and lab meetings and provide guidance and inputs on experiment design and accurate statistical inference
- Will have a responsibility to work with the BIDS PAO as may be required
This position may be filled with a Bioinformatics Analyst II/III commensurate with the selected candidates experience.
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) or four (4) years relevant experience in lieu of degree. Foreign degrees must be evaluated for U.S. equivalency
- Bioinformatics Analyst II - In addition to the education requirement, a minimum of two (2) years of progressively responsible experience
- Bioinformatics Analyst III- In addition to the education requirement, a minimum of five (5) years of progressively responsible experience
- Some knowledge of Unix command line or scripting languages
- Must be able to obtain and maintain a clearance
Candidates with these desired skills will be given preferential consideration:
- Possession of a Masters’ (Analyst II) or Ph.D. (Analyst III) degree in any quantitative science is preferred
- Commitment to solving biological problems and communicating these solutions
- Ability to multi-task across projects
- Experience in submitting data sets to public repositories
- Management of large genomic data sets including integration with data available from public sources
- Prior customer-facing role
- Record of scientific achievements including journal publications and conference presentations
- Experience evaluating and comparing different computational pipelines for alignment, variant calling, and functional annotation
- Deep understanding of and experience in processing high throughput biomedical data: data cleaning, normalization, analysis, interpretation, and visualization
- Ability to understand and analyze data from complex experimental designs
- Proficiency in at least two of the following programming languages: Python, R, Perl, Java, and C/C++
- Experience in at least two of the following areas: Exome sequencing, metagenomics, ChIPSeq, RNASeq, DHS-Seq, microarray analysis, DNA methylation analysis, single-cell transcriptomics
- Familiarity with public databases: NCBI, Ensembl, TCGA, cBioPortal, Broad FireHose
- Knowledge of working in a cluster environment
Equal Opportunity Employer (EOE) | Minority/Female/Disabled/Veteran (M/F/D/V) | Drug Free Workplace (DFW)