Postdoctoral Researcher – Integrative Genetics and Multi-Omics Data Science

We are seeking a highly motivated and innovative postdoctoral researcher to join the Precision Genetics group within the Data, AI and Genome Sciences (DAGS) department at our company. The successful candidate will develop and apply scalable computational and statistical methods for biobank-scale multi-modal data analysis and biomarker discovery, integrating human genetics, proteomics, electronic health record (EHR) data, and other large-scale clinical and molecular datasets.

The role will also involve developing genetics-informed causal modeling frameworks by integrating human genetics and genomics data with perturbation-based sequencing datasets in close collaboration with the Genome Science group, with co-mentorship across teams. This unique role aims to uncover causal gene–pathway–disease relationships, identify disease- and target-associated biomarkers, and advance translational research across multiple therapeutic areas.

• Develop scalable computational pipelines for integrating genetics, proteomics, EHR, and other biomedical datasets to support target and biomarker discovery.
• Develop robust statistical and computational methods for causal modeling by integrating human genetics, genomics, and perturbation datasets.
• Analyze biobank-scale datasets and support interpretation of associations and candidate biomarker signals.
• Track cutting-edge computational and statistical methods in statistical genetics and computational biology, and proactively propose and pilot innovative ideas and approaches.
• Collaborate closely with wet-lab scientists and cross-functional computational teams.
• Communicate findings effectively through peer-reviewed publications, internal and external presentations, and collaborative meetings within the department and across functions in our company.

Minimum Requirement:
Must currently hold a PhD OR Receive a Ph.D. no later than spring 2027 Ph.D. in Statistics, Biostatistics, Statistical Genetics, Genetic Epidemiology, Computational Biology, Bioinformatics, Computer Science, Mathematics, or a related quantitative field.

• Demonstrated experience working with large-scale biobank or consortium phenotypic, genetic, genomic, and biomarker datasets such as UK Biobank, Our Future Health, All of Us, Finn Gen, etc.
• Demonstrated experience analyzing large-scale omics datasets, including whole-genome sequencing (WGS), genome-wide genotyping data, transcriptomics, proteomics, or other molecular data types.
• Hands‑on experience applying and/or developing statistical genetics methods such as GWAS, QTL mapping, polygenic scores, etc.
• Proficient programming skills in R and/or Python for data analysis, statistical modeling, and pipeline development.
• Cloud platforms (e.g., AWS) or HPC environments, including parallel computing, job scheduler, and scalable workflow design.
• Excellent written and oral communication skills, with a demonstrated ability to publish methodological papers or innovative applications in statistical genetics, computational biology, or related fields.

The salary range for this role is: $82,000- $92,000. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs.

The successful candidate will be eligible for annual bonus and long-term incentive, if applicable. We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other…