About the Role

We're seeking a Genetics Scientist (Whole Genome Sequencing) to assist with WGS data processing and variant discovery for precision medicine programs targeting Parkinson’s disease risk and progression for GP2. You'll drive large-scale joint calling pipelines and execute sophisticated variant analyses including short tandem repeats (STRs), structural variants (SVs), and rare variant burden tests at biobank scale.

What You'll Do

Primary Responsibilities (70%)

• Assist with quality control and processing of WGS data from diverse cohorts from around the world
• Perform joint calling (DRAGEN) and other pipelines (Gauchian, STR, SV, and others)
• Help prepare data to be released to researchers as part of a bi-annual data release schedule
• Execute rare variant burden tests (REGENIE) for coding and regulatory variants
• Perform variant annotation and functional prediction using VEP, SnpEff, CADD, and splice prediction tools
• Write and publish papers based on rare variant and SV analyses

Secondary Responsibilities (30%)

• Collaborate with GWAS team to follow up loci with WGS characterization
• Support multi-omic integration and follow-up
• Assist GP2 contributing cohorts with analyses in their cohorts and other monogenic analyses being conducted by GP2
• Contribute to training efforts and materials where necessary

Required Qualifications

• MS or PhD in Human Genetics, Computational Biology, Bioinformatics, Genomics, or related quantitative field
• Published experience with WGS data processing and variant discovery (first-author publications demonstrating technical expertise)
• Expert-level proficiency in WGS variant calling pipelines
• Strong command of STR analysis tools (ExpansionHunter, GangSTR, HipSTR, or similar)
• Experience with structural variant callers
• Proficiency in rare variant burden testing frameworks (SAIGE-GENE, REGENIE, RVAT, or similar)
• Expert knowledge of variant annotation tools (VEP, SnpEff, ANNOVAR) and functional prediction databases
• Proficiency in R and/or Python for genomic data analysis and visualization
• Hands-on experience with cloud-based genomics platforms (e.g., Terra, Verily Workbench, UK Biobank Research Analysis Platform, DNAnexus, or equivalent)
• Strong understanding of population genetics principles (allele frequency, linkage disequilibrium, Hardy-Weinberg equilibrium)
• Track record of working with biobank-scale WGS datasets (10K+ samples)

Preferred Qualifications

• Experience with Parkinson's, Alzheimer's, or neurodegenerative disease genetics
• Familiarity with repeat expansion disorders and known pathogenic STRs (C9orf72, HTT, ATXN2, etc.)
• Experience with multi-ancestry WGS data and population-specific variant interpretation
• Knowledge of non-coding variant interpretation and regulatory element analysis
• Experience with long-read sequencing data (PacBio HiFi, ONT) for complex variant resolution
• Publications in high-impact genetics or genomics journals
• Experience with workflow languages (WDL/Cromwell, Nextflow, Snakemake)

Technical Environment

You'll work in cloud-native genomics environments including Terra, Verily Workbench, and the UK Biobank RAP. Familiarity with WDL/Cromwell or Nextflow workflows is strongly preferred. We leverage both CPU and GPU compute for large-scale analyses in the cloud.

To Apply

Submit CV and cover letter with links to 2-3 representative publications demonstrating WGS processing and analysis expertise as well as related GitHub content.

Compensation

$100,000 to $200,000 / year total compensation commensurate with experience.