Machine Learning Scientist - Graph ML/GNN's
Join to apply for theMachine Learning Scientist - Graph ML/GNN'srole atRelation.
About Relation
Relation is an end-to-end biotech company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics directly from patient tissue, functional assays, and machine learning to drive disease understanding—from cause to cure.
Opportunity
Join the Turing team as a Machine Learning Scientist, where you will develop cutting-edge ML methods, including graph machine learning, reinforcement learning, and large language models (LLMs). This role is ideal for a technically skilled ML expert with experience in applying these areas of machine learning to complex data challenges.
The team you will become part of
The Turing team focuses on leveraging advanced machine learning techniques, such as graph ML, recommender systems, and multi-agent reasoning systems, to transform drug discovery. The team’s work integrates computational insights across diverse domains, accelerating therapeutic development and improving decision-making in Target Discovery and Validation.
Your Responsibilities
- Design and implement graph-based models for drug discovery applications.
- Collaborate with interdisciplinary teams to translate ML approaches into actionable insights.
- Develop scalable computational frameworks for analysing large-scale biological and clinical data.
- Contribute to the broader ML community through research publications and conference presentations.
- Ensure delivery of high-quality ML projects by adhering to best practices and modern engineering standards.
Professionally, you have
- PhD in machine learning, data science, or a related field, or equivalent industrial experience.
- Expertise in graph machine learning.
- Proficiency in Python and frameworks like PyTorch.
- Experience developing scalable ML solutions for complex datasets.
- A track record of delivering ML projects in industry or academia.
Desirable Knowledge Or Experiences
- Exposure to recommendation systems and/or multi-agent setups.
- Familiarity with integrating ML techniques into drug discovery pipelines.
Personally, you are
- Inclusive leader and team player.
- Clear communicator.
- Driven by impact.
- Humble and hungry to learn.
- Motivated and curious.
- Passionate about making a difference in patients’ lives.
Join us in this exciting role, where your contributions will directly impact advancing our understanding of genetics and disease risk, supporting our mission to deliver transformative medicines to patients. Together, we’re not just conducting research—we’re setting new standards in the fields of machine learning and genetics. The patient is waiting!
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