About the position
The Complex Disease Genetics (CDG) group within our Company's Data, AI and Genome Sciences (DAGS) Department is seeking motivated Senior Scientists to support our Cambridge-based research initiatives in complex disease genetics. We welcome applications from scientists with a graduate degree (PhD or equivalent) in statistical genetics, genetic epidemiology, computational biology, biostatistics, or a related field. The ideal candidate will have hands-on experience with human genetics and multi-omics data analysis and a strong interest in translational research for drug discovery and precision medicine. As a key member of the Precision Disease Genetics group, you will contribute to the analysis of large-scale public and proprietary datasets-including population-based biobanks, patient cohorts, and family-based studies-integrating genetic, genomic, and clinical data. Our Company has invested in external partnerships and collaborative initiatives to accelerate innovation in drug discovery and development. The CDG group leverages large-scale data resources, such as FinnGen, the Alliance for Genomic Discovery, Our Future Health, UK Biobank Pharma Proteomics Project, Open Targets, and other public and proprietary datasets, to advance our Company's drug development pipeline through human genetics. Your work will contribute to our Company's drug development efforts by supporting target identification and validation and the implementation of precision medicine strategies across therapeutic areas. You will have the opportunity to work collaboratively with internal and external partners and to develop your expertise in human genetics and translational research.
Responsibilities
- Perform statistical genetics analyses for target discovery and validation using human genetics, multi-omics, and real-world data
- Support the development, implementation, and maintenance of analytical pipelines for reproducible genetic and genomic data analysis
- Conduct genetic association analyses using large-scale biobank data (e.g., UK Biobank, FinnGen, Our Future Health, Alliance for Genomic Discovery)
- Integrate and analyze public and proprietary genetic association summary statistics and conduct meta-analyses
- Perform post-GWAS analyses to help elucidate causal mechanisms and prioritize gene targets (e.g., fine mapping, colocalization, Mendelian Randomization, TWAS, polygenic risk prediction)
- Assist in integrating genetic association findings with multi-omics data (e.g., RNA-seq, ATAC-seq, QTLs) to support target prioritization
- Stay current with new methods in statistical genetics and participate in evaluating and implementing emerging analytical techniques
- Collaborate with wet-lab biologists, disease area experts, and data scientists to support research and patient stratification strategies
- Communicate scientific findings to internal teams and contribute to publications and presentations
Requirements
- PhD (or equivalent) in statistical genetics, genetic epidemiology, computational biology, biostatistics, or a related discipline, with some postdoctoral or equivalent research experience in complex disease genetics or related area
- Will consider candidates with either genetics/genomics background or real-world data background
- Research experience in human genetics, genomics, or related analysis, including genome-wide association studies (GWAS) and/or multi-omics analysis
- Familiarity with analytical pipelines and best practices for reproducibility and scalability in genetic data analysis
- Proficiency in programming languages commonly used in statistical genetics (e.g., R, Python, etc.)
- Experience working with large-scale datasets in cloud-based computing and high-performance computing environments
- Experience with complex phenotypes and/or real-world data (e.g., electronic health records, imaging, digital biomarkers)
- Exposure to molecular phenotypes, such as transcriptomics or proteomics
- Strong communication and interpersonal skills, with the ability to work effectively in multidisciplinary teams
Nice-to-haves
- Interest or background in neuroscience, cardiovascular/metabolic diseases, immunology, or other complex diseases
Benefits
- Medical, dental, vision healthcare and other insurance benefits (for employee and family)
- Retirement benefits, including 401(k)
- Paid holidays, vacation, and compassionate and sick days
