Principal Scientist, Statistical Genetics
Core
Lead implementation of statistical genetics approaches to identify and validate drug target candidates for cardiovascular diseases using large-scale human genetic data.
Role type
Principal Scientist, Statistical Genetics
Builds
Therapeutic hypotheses and drug target candidates for cardiovascular disease programs
Domain
Biopharmaceuticals / Cardiovascular Disease / Statistical Genetics
Deliverable
production ML models
Required skills
Statistical genetics methods (GWAS, fine-mapping, colocalization, Mendelian Randomization, rare variant association tests, polygenic modeling), Causal inference, Drug target discovery, Cross-biobank analysis, Integrative multi-modal data analysis, Scientific communication
Preferred skills
PhD in statistical genetics or related field, Experience applying genetics to drug discovery, Functional genomics knowledge, Advanced programming in R or Python
Technologies
R, Python, GWAS, UK Biobank, FinnGen
Responsibilities
Design and perform cross-biobank analyses to identify human genetic risk factors for cardiovascular diseases; Design and perform integrative analyses to infer causal mechanisms using human genetics and other data types; Leverage disease-specific multi-modal datasets from consortia; Coordinate with stakeholders to nominate and advance novel drug targets; Communicate findings and recommend follow-up actions in meetings and publications
Seniority
Principal, hands-on IC
