Lead AI/ML Scientist – Human Genetics & Genomics

CamWebDir; Cambridge; Hybrid; GBP 65,000 - 85,000; Full time

Benefits offered by this job

Hybrid working

Wellbeing programme

Campus-wide benefits

Job summary

The Wellcome Sanger Institute seeks a Principal Staff Scientist (computational) to lead AI/ML across the Human Genetics Programme. You will shape analytical strategy and sit on the Programme Working Group, driving models from data to clinical application with strong collaboration across genetics, proteomics, metabolomics and clinical data.

You will oversee projects spanning scRNA-seq, whole-genome sequencing and multiomic data, contributing hands-on coding and analysis while mentoring scientific

Qualifications

• PhD in statistical genetics, computational biology, statistics, ML, epidemiology or related quantitative discipline.
• Substantial expertise in AI/ML methods for disease predictors from high-dimensional data.
• Experience analyzing human genetic and genomic data at scale.
• Proven independent research record with publications and outputs.
• Able to write code and analyze data personally.

Responsibilities

• Provide strategic direction for AI/ML across the Programme.
• Lead development and validation of predictive models for clinical use.
• Ensure analytical consistency and reusable tools across projects.
• Lead on IBD projects in the Anderson group and collaborate with clinical/industry partners.

Skills

PhD in quantitative science

AI/ML for disease prediction

Genomic data analysis at scale

Independent research leadership

Code & data analysis

Collaborations & leadership

Excellent communication

Diversity & inclusion

Education

PhD in quantitative discipline

Tools

Git

Python/R

Job description

The Wellcome Sanger Institute seeks a Principal Staff Scientist (computational) to lead AI/ML across the Human Genetics Programme. You will shape analytical strategy and sit on the Programme Working Group, driving models from data to clinical application with strong collaboration across genetics, proteomics, metabolomics and clinical data.

You will oversee projects spanning scRNA-seq, whole-genome sequencing and multiomic data, contributing hands-on coding and analysis while mentoring scientific