Bioinformatics Scientist

Location
Gaithersburg, MD, USA
Posted
Nov 22, 2018
Ref
JR78-21197
Hotbed
BioCapital
Required Education
Doctorate/PHD/MD
Position Type
Full time
The Cancer Genomics Research Laboratory (CGR) investigates the contribution of germline and somatic genetic variation to cancer susceptibility and outcomes in support of the National Cancer Institute (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. This includes the design and analysis of high throughput studies using various types of “-omics” technologies such as sequence- and array- 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.

Key Roles/Responsibilities: The Position Title - Bioinformatics Scientist

The Cancer Genomics Research (CGR) Laboratory is a fast-paced, high throughput facility dedicated to the support of genetic and epidemiologic studies for investigators at the National Cancer Institute.

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 successful incumbent will provide independent and strong support to the extensive DCEG sequencing analytical efforts, specifically:
  • Performing curation, QC, harmonization and evaluation of large scale whole genome sequencing (WGS) tumor/normal data
  • Performing a wide range of bioinformatics analyses for WGS tumor/normal data including germline and somatic SNV/indel calling, Structure Variant (SV) detection, Copy Number Variation (CNV) detection, and other DNA sequencing related analyses
  • Performing downstream analyses including variant filtering/validation, burden test, statistical analysis, and integrative analysis
  • Identifying, evaluating and implementing the state of the art bioinformatics tools to fulfill various sequencing based analytical needs
  • Developing new bioinformatics tools through adequate benchmarking and QC
  • Organizing results into clear presentations and concise summaries of work, in formats useful for scientific interpretation
  • Working closely with DCEG PIs in support of scientific manuscript development, submission, revision activities with significant coauthorship and potentially lead authorship opportunities

Basic Qualifications:

To be considered for this position, you must minimally meet the knowledge, skills, and abilities listed below:
  • Possession of a Doctoral degree from an accredited college/university in Bioinformatics, Computer Science, Computation Biology, or related field. Foreign degrees must be evaluated for U.S equivalency
  • In addition to educational requirements, a minimum of two (2) years of progressively responsible scientific and/or complex system management/bioinformatics experience including sequencing/genomics analysis
  • High programming proficiency in Shell, Python, R, Java, and/or C
  • Experience with human DNA-seq data, tumor/normal analysis using a wide range of contemporary, open-source/commercial bioinformatics tools such as GATK, Muse, SomaticSeq, Manta, Meerkat, FACETS, ASCAT, Plink, etc.
  • Experience with High-performance computing and large-scale data processing
  • Experience with software development on Linux system


Preferred Qualifications:
  • Candidates with these desired skills will be given preferential consideration:
  • Experience with AWS EC2/ELB/S3 or other cloud computing environments
  • Experience with Snakemake or other workflow languages
  • Experience with Singularity or other container-based platforms
  • Experience with statistics and algorithm development
  • Experience with publicly available data sources (such as dbGaP, TCGA, GDC, ENCODE, 1000 Genomes, gnomAD, TARGET, GTEX) and diverse genomic annotations
  • Experience with MySQL/MS SQL Server or other relational databases
  • Experience with RNA sequence and Methylation analysis
  • Experience with molecular and population genetics


Equal Opportunity Employer (EOE) | Minority/Female/Disabled/Veteran (M/F/D/V) | Drug Free Workplace (DFW)