Statistical Genetics Intern (AI/ML)

TL;DR

Statistical Genetics Intern (AI/ML): Analyzing cutting-edge genomic datasets using GWAS and rare variant association studies with an accent on developing novel statistical or machine learning methods. Focus on creating and validating polygenic risk scores, annotating genetic variants, and curating phenotypic information to understand disease biology.

Location: Cambridge, UK (Hybrid/Remote). Sponsorship is not provided for this role.

Company

hirify.global is a global biopharmaceutical company dedicated to transforming the lives of patients with serious and rare diseases.

What you will do

• Analyze genomic datasets using GWAS and rare variant association studies.
• Develop novel statistical or machine learning methods for genetic and phenotypic analysis.
• Create and validate polygenic risk scores for rare disease phenotypes.
• Develop and curate phenotypic information to aid in understanding disease biology.
• Annotate and prioritize genetic variants using advanced computational tools.

Requirements

• Currently pursuing an MS or PhD in Statistical Genetics, Biostatistics, Data Science, Machine Learning, Computational Biology, or a related field.
• Strong foundation in statistical genetics principles.
• Proficiency in R or Python, and familiarity with genetic analysis tools (e.g., PLINK, BOLT-LMM, SAIGE).
• Experience with genomic data formats and Linux/Unix environments.
• Ability to commit full-time (40h/week) from June 23rd to September 11th, 2026.
• Must have existing right to work in the UK; no sponsorship available.

Nice to have

• Knowledge of rare diseases.
• Understanding of RNAseq.
• Experience curating ICD-10 or other medical coding data.
• Cloud or high-performance computing (HPC) experience.

Culture & Benefits

• Paid internship including company holidays.
• Hands-on experience with cutting-edge genetic research in a biotech setting.
• Mentorship from a diverse team of experts in data science, AI, ML, and human genetics.
• Collaborative and innovative work environment focused on patient impact.
• Networking opportunities with leaders and a final project presentation.