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Computational Scientist I - Genome Wide Assoc. Studies (GWAS) (req1646)

Company: Frederick National Laboratory
Location: Rockville
Posted on: July 15, 2021

Job Description:


  • Perform large-scale genotyping data QC, phasing and imputation, population structure testing, association studies, meta-analysis, and fine mapping
  • Contribute to building, benchmarking, and maintaining bioinformatics pipelines to facilitate high-throughput genomic data analysis in HPC and cloud environments
  • Harmonize and maintain diverse datasets and associated metadata, including performing meta-analyses of data run on multiple platforms and/or externally generated data
  • Thoughtfully synthesize results into clear presentations (including QQ-plots, Manhattan plots) and concise summaries of work to support recommendations for next steps
  • Perform advanced research including multiplicative interaction studies, pathway-based studies, and integrative analyses from multiple platforms and various data types
  • Collaborate closely with DCEG PIs on scientific manuscript development, submission, and revision activities with significant co-authorship and potentially first authorship opportunities

  • Possession of a Doctoral degree from an accredited college/university in bioinformatics, statistics, genetics, computational biology or related field. Foreign degrees must be evaluated for U.S equivalency.
  • No experience required beyond a doctoral degree.
  • In-depth knowledge of genome-wide association studies and interpretation, and applied computational research on large multivariate datasets
  • Expertise in algorithmic implementation, statistical programming and data manipulation, using e.g. R/Bioconductor, Python, MATLAB, and a wide range of contemporary, open-source bioinformatics tools (e.g. PLINK, SNPTEST, IMPUTE2, BEAGLE, UCSC Genome Browser, Michigan Imputation Server, etc.)
  • Proficiency with Bash, Python, Perl, R, C/C++, and/or JAVA
  • Team-oriented with excellent written and verbal communication skills, organizational skills, and attention to detail; ability to organize and execute multiple projects in parallel
  • Demonstrated ability to proactively remain up-to-date in current bioinformatics techniques and resources, and identify and benchmark novel software solutions against established reference datasets
  • Experience in constructing practical computational tools/pipelines for data parsing, quality control, modelling, and analysis for large-scale genetic or genomics datasets
  • Ability to obtain and maintain a security clearance

  • Familiarity with publicly available data sources (such as dbGaP, GDC/TCGA, ENCODE, 1000 Genomes, gnomAD/ExAC, TARGET, GTEX) and diverse genomic annotations
  • Experience managing large datasets and computational tasks in a Linux-based high-performance computing environment
  • Pipeline development experience, including collaborative coding and use of source control (e.g. git)
  • Experience with Snakemake, make, or other workflow management systems
  • Experience with containerization (e.g. Singularity, Docker)
  • Experience with Google Cloud, AWS, or managed cloud environments
  • Experience in the field of molecular and population genetics with a strong publication record

Keywords: Frederick National Laboratory, Rockville , Computational Scientist I - Genome Wide Assoc. Studies (GWAS) (req1646), Other , Rockville, Maryland

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