Biomedical AI Researcher Multi-Omics & Population Genomics

University of Cambridge; Cambridge; On-site; GBP 42,000 - 52,000; Full time

Benefits offered by this job

Flexible working hours

Commitment to equity and inclusion

Job summary

University of Cambridge seeks a postdoctoral biomedical data scientist to lead AI model development in the Cardiovascular Epidemiology Unit and CBSGI. The role focuses on predicting biologically meaningful parameters from genomic and multi-omic data at population scales, with potential for grant-funded expansion.

You will apply deep learning and ML methods, conduct quantitative analyses, and contribute to first-author publications while collaborating across departments in a flexible,

Qualifications

• PhD in data science or related field.
• Experience with deep learning and machine-learning models.
• Strong quantitative analysis skills (in silico).
• Proficiency with R and/or Python; experience on computing clusters.

Responsibilities

• Lead projects developing new AI models and benchmark existing ones.
• Scale models for population-level data (e.g. >1 million individuals).
• Perform quantitative analysis of genomic, multi-omic and phenotypic data (polygenic scores, GWAS, Mendelian randomisation).

Skills

Deep learning

Machine learning

Quantitative analysis

R programming

Python programming

Linux

Computing clusters

Education

PhD in data science or related field

Tools

R

Python

Linux

Computing clusters

Job description

University of Cambridge seeks a postdoctoral biomedical data scientist to lead AI model development in the Cardiovascular Epidemiology Unit and CBSGI. The role focuses on predicting biologically meaningful parameters from genomic and multi-omic data at population scales, with potential for grant-funded expansion.

You will apply deep learning and ML methods, conduct quantitative analyses, and contribute to first-author publications while collaborating across departments in a flexible,