Bioinformatics Analyst – Statistical Genomics

Job ID
Epidemiology & Cancer Control
Job Location


The Department of Epidemiology and Cancer Control at St. Jude Children’s Research Hospital is seeking a highly qualified and motivated Bioinformatics Analyst with a demonstrated expertise in computational and statistical genomics to study the genetic and biological mechanisms underlying long-term toxicities of cancer treatments among survivors of childhood cancer.


The successful candidate will have a strong background in statistical genetics/genomics, biostatistics, computational genomics, bioinformatics, or a related quantitative field, and strong programming skills, and should be excited to contribute to advancing the science and pharmacogenomics of treatment-related late effects in childhood cancer survivors. Research projects will involve creating pipelines and analyzing large-scale omics data including, but not limited to, whole genome and whole exome sequencing, RNA-seq, ATAC-seq, proteomics and metabolomics, in relation to the clinical phenotypes. Strong research experience in genome-wide association studies (GWAS) of common and rare variants (both NGS and chip-based genotype) data and eQTL mapping is required. Proficiency in statistical genetics/genomics software including PLINK, GATK, matrixeQTL, and at least one of more programming languages such as R, Python, Perl, Java, or C++ under Linux/Unix environment is required. Familiarity with large genetic databases such as the UK Biobank, 1000 Genomes Project, gnomAD and others is desired. 


The department provides a highly interactive environment with collaborative opportunities, access to high performance computing clusters, a cloud computing environment, innovative visualization tools, highly automated analytical pipelines and mentorship from scientists with interests experience in data analysis, data management and delivery of high-quality results. The Department of Epidemiology and Cancer Control supports strong teamwork as well as individual and personal growth. 


Please include a cover letter including responses to the required skills/qualifications.



  • Perform genetic association analyses using WGS/WES data to identify genetic factors associated with treatment-related long-term toxicities in childhood cancer survivors
  • Build polygenic risk scores and evaluate their ability in predicting the risk of developing long-term toxicities in childhood cancer survivors
  • Develop and apply new statistical and computational methods that integrate multi-omics data with GWAS studies to gain biological insights into the causal mechanisms underlying adverse effects in survivors
  • Stay informed about new methods in computational and statistical genomics and understand how to apply them appropriately
  • Critically review, analyze, summarize, and communicate results of analyses to research faculty, staff, and clinical collaborators
  • Interpret results; identify potential problems and their solutions
  • Prepare results for publications, work with collaborators in writing publications and, in some cases, take the lead in writing publications
  • Organize all scripts in a publicly available repository (eg. Github) with clear documentation

Minimum Education

  • Bachelor's degree is required. Master's degree or PHD is preferred

Minimum Experience

  • Two (2) years of relevant experience is required
  • No experience may be acceptable with a Master’s degree or PHD in Statistical/Computational Genomics or Bioinformatics, with a background in the biological sciences
  • Experience with approaches used to understand complex trait genetics, such as GWAS, rare-variant analysis, Mendelian Randomization, LD Score regression, eQTL mapping, polygenic risk score modelling and cross-trait analyses
  • Strong research experience in large-scale genomic datasets (RNA-seq, ATAC-seq, CHIP-seq, etc.)
  • Strong research experience in post-GWAS analysis (locus to gene mapping and fine mapping)
  • Statistical programming skills (such as R)
  • Programming/scripting skills (such as Python/Shell/Others)
  • Experience in statistical data analysis of large data sets efficiently using parallel computing locally in a cluster environment and in a cloud environment
  • Experience in development of algorithms, statistical methods or scientific software is preferred
  • Experience working on a team project is preferred
  • Work on both collaborative and independent projects and write up work for publications
  • Demonstrated critical thinking, rigorous work, and ability to meet deadlines
  • Strong personal skills and excellent organizational and verbal and written communication skills
  • Ability to work effectively in a fast-paced, academic environment and evolving field

What We Offer



Salary is highly competitive (comparable to industry) and employee benefits are outstanding. Relocation assistance is available. Working at St. Jude provides the opportunity to make a tangible difference to pediatric cancer patient care and survival and St. Jude has been consistently ranked in Fortune magazine’s “100 Best Places to Work” list and is exceptionally positively reviewed on GlassDoor.



WHATWE_Benefits         WHATWE_Glassdoor         WHATWE_UnexpectedPerks




Other Information

COVID-19 vaccine:


As of September 10, 2021, St. Jude Children’s Research Hospital has mandated the COVID-19 vaccine for all employees, excluding those with an approved medical or religious accommodation, as a condition of employment.


EEO Statement:  St. Jude is an Equal Opportunity Employer

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