Data Scientist, Antibody Design (12-month FTC) in London

About Relation

Relation is a sector‑defining TechBio 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 from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state‑of‑the‑art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact.

We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients.

The opportunity

Relation is offering an outstanding opportunity for a Data Scientist to support computational drug discovery and drug‑ability efforts focused on antibodies. You will work closely with external deep‑learning‑driven antibody design platforms to critically evaluate generated candidates, extract insights, and integrate learnings into internal discovery strategies.

Day to day, you will:

• Support computational antibody discovery and drug‑ability efforts across research programmes.
• Work with internal and external teams to evaluate and interpret computationally generated antibody candidates.
• Contribute computational and structural biology expertise to multidisciplinary project teams.
• Help extract insights from sequence, structural, and modelling data to inform discovery decisions.
• Collaborate with machine learning and experimental scientists to support ongoing research activities.
• Contribute to the development and refinement of internal computational discovery strategies and workflows.

Professionally, you will have:

• A PhD in computational biology, structural bioinformatics, computational structural biology, or a related field; or a Master’s degree with equivalent industry experience.
• 0–2 years of experience in biotech, pharma, or a relevant postdoctoral environment.
• Experience with computational approaches for antibody design and development.
• Antibody sequence and repertoire analysis.
• Structural modelling of antibodies and antibody‑antigen complexes.
• Computational protein engineering and affinity optimisation.
• Machine learning and generative modelling for antibody design.
• Developability and biophysical risk assessment.
• Knowledge of Python as a programming language.
• Understanding of the drug discovery process.
• Bonus experience: Exposure to real‑world drug discovery projects; experience with additional therapeutic modalities such as small molecules, nucleic acids, or degraders; exposure to machine learning.

Personally, you:

• Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams.
• Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work.
• Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect.
• Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams.
• Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes.

Working Style & Culture at Relation

At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting!

Relation is a committed equal opportunities employer.