Bio/ML Internship

The role

We are seeking a motivated Bio/Machine Learning intern to join our team working at the interface of biology and data science. This paid internship offers hands-on experience in applying computational, statistical, and machine-learning methods to solve real-world problems in drug discovery and target safety assessment.

As an intern, you will take ownership of a defined project within the platform, shaped around your background and interests, with the support of a multidisciplinary team. 

What you’ll do:

• Analyse and integrate biological datasets (e.g.clinical data, functional genomics, mechanistic data) to support target safety assessment

• Develop or extend computational pipelines for processing, validating, and analysing biomedical data for use in Sable platform models and features

• Apply statistical or machine-learning methods to quantify and prioritise biological risks

• Interpret results in a biological and translational context, with a focus on supporting drug discovery decision-making

• Collaborate with software engineers to turn analyses into Sable platform features, used directly by by toxicologists and drug discovery scientists

• Contribute to a shared codebase alongside scientists and engineers, following good software and data-engineering practices

We are looking for candidates who are eager to learn, can work independently, and have a strong interest in applying computational methods to healthcare challenges.