Principal Computational Methodologist (UK)

Overview

In this role, you shape how advanced AI, ML, and computational methods support clinical development. You will design and validate models that inform biomarker discovery, trial design, and patient experience, then deploy scalable tools for cross-functional teams.

You’ll translate complex methods into practical solutions while meeting scientific, technical, and regulatory standards. You will work with diverse partners to advance evidence-based decision making and publish impactful findings.

This position offers a meaningful opportunity to drive value for patients through innovative data science.

Pay / Benefits

• hybrid-first work model
• equal opportunity employer
• global presence and collaboration
• growth and career development
• supportive, inclusive culture
• values-driven mission

Responsibilities

• Lead AI and ML projects addressing clinical development, biomarker, operational, and decision-support needs
• Design, build, test, and refine deep learning models for text, graphs, biological sequences, and clinical data
• Develop generative AI applications using foundation models and large language models
• Run rigorous, reproducible AI experiments on internal and public datasets to generate publishable results
• Partner with engineering to package methods into applications, platforms, and scalable validated solutions
• Mentor colleagues and represent the team in publications, presentations, and external collaborations

Key requirements

• PhD in a related field
• Industry experience, ideally in pharma, clinical development, or regulated data environments
• Proficiency in Python, R, or similar languages; ability to guide others in coding
• Knowledge of supervised, unsupervised, Bayesian, and deep learning approaches
• Experience with ML infrastructure, reproducible research, Linux/HPC, and software/platform development
• Strong communication with scientific, technical, medical, and business partners; collaborative mindset
• collaborative
• curious
• impact-driven
• Python
• R
• deep learning

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