Scientist
Core
Early-career scientist developing therapeutic targets and patient stratification strategies using genomic data and AI/ML.
Role type
Early-career scientist (Life Sciences)
Builds
Therapeutic development programs and patient risk stratification tools
Domain
Biotechnology / Genomics / Drug Discovery
Deliverable
production ML models | research
Required skills
Statistics (modelling, regression), Genetics and molecular biology, Statistical programming (Python or R)
Preferred skills
Statistical genetics approaches (GWAS, colocalization, fine-mapping, Mendelian randomization, polygenic risk scores), Phenotype definition from EHRs, Bayesian inference, high dimensional statistics, causal inference, Software engineering practices (Git, testing, documentation, containerisation), Reproducible pipelines (WDL, Snakemake, NextFlow), Cloud computing (DNAnexus, Verily Workbench), Methods development in statistical genetics
Responsibilities
Generate novel therapeutic hypotheses by mining in-house data resources to understand disease pathophysiology and identify targets, Apply and optimize risk tools combining genetic information with conventional risk factors for patient stratification
Seniority
Early-career, hands-on IC
