Statistical Geneticist with Machine Learning

We are partnered with a cutting-edge Biotech who are researching and modelling health resilience, unlocking novel therapies . Combining large-scale human genetics, multi‑omics, and AI, they are driving target discovery and accelerating drug development in partnership with leading pharma companies.

They are hiring a Statistical Geneticist with Machine Learning experience to contribute to their genetics‑driven causal AI platform:

Responsibilities

• Lead GWAS, PheWAS, PRS, rare variant and post‑GWAS analyses
• Integrate multi‑omics QTL data (eQTL, pQTL, mQTL) for gene prioritisation and causal inference
• Working with and Apply ML‑derived and continuous phenotypes to enhance genetic discovery
• Build scalable, reproducible pipelines for population-scale datasets
• Work cross‑functionally with ML, biology, and engineering teams to drive drug discovery decisions

Requirements

• MSc or PhD in Statistical Genetics, Bioinformatics, Biostatistics, Computational Bio or similar.
• First authorships on published papers related to ML and/or StatGen
• Demonstrated skills & experience in Python/PyTorch, R, Unix/Linux, and GWAS methodologies
• Experience with HPC or cloud computing
• Experience in deep learning or ML.

Please apply with an updated CV to be considered for the position. Be prepared to talk through your skills and experience which aligns with the position.

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