Full-Time Research Scientist Statistical Genetics
Deep Genomics is hiring a remote Full-Time Research Scientist Statistical Genetics. The career level for this job opening is Experienced and is accepting North America based applicants remotely. Read complete job description before applying.
Deep Genomics
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About UsDeep Genomics is using AI to transform drug discovery. Our AI platform decodes RNA biology to find new drug targets and therapies. Our team is in Toronto and Cambridge, MA.
Your RoleYou'll use large human genetic datasets (whole genome, exome, array) for finding genetic targets and patient groups. You'll develop and use analysis methods and work with machine learning scientists to combine AI with traditional methods. You'll collaborate with statistical genetics, bioinformatics, and biology teams to prioritize targets. We seek a PhD in statistical genetics with 2+ years of experience. Passion for AI's potential in drug discovery is essential.
Responsibilities
- Perform advanced analyses (GWAS, PheWAS, rare variant burden, Mendelian randomization)
- Improve post-hoc analysis to prioritize potential targets
- Integrate AI-powered variant predictors with traditional methods
- Create containerized software workflows on Google Cloud Platform
- Collaborate on projects to enhance genomic AI models
- Translate findings into biological insights for target and patient prioritization
- Participate in code review and testing
Qualifications
- PhD in human statistical genetics (or related) with 2+ years of experience
- Publication record
- Large-scale human genetic association analysis experience (WGS, WES, GWAS, PRS)
- Strong programming skills (Python preferred)
- High-throughput or cloud compute experience (especially GCP)
- Understanding of human genetics and basic biology
- Critical thinking, curiosity, and commitment to innovation
- Strong communication and interpersonal skills
Preferred Qualifications
- Post-graduate experience (academia or industry)
- UK Biobank experience
- Experience with variant effect predictors and AI/ML models
- Familiarity with systems biology or single-cell sequencing
- Experience integrating multi-modal data
What We Offer
- Collaborative and innovative environment
- Competitive compensation and meaningful stock ownership
- Comprehensive benefits
- Flexible work environment
- Top-up maternity/parental leave and new parent paid time off
- Learning and development budget and lunch and learns
- Toronto/Cambridge locations