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About the Role

Qureight is building a machine learning research capability to develop robust, clinically meaningful models for 3D medical imaging as the company scales its AI-driven platform and expands its work with pharmaceutical and clinical partners. This role focuses on foundation-model pre-training, supervised model specialization, segmentation, classification, regression, and biomarker extraction pipelines supporting clinical-trial and real-world evidence programs.

Responsibilities

Research, develop, and evaluate state-of-the-art computer vision methods for volumetric CT data.
Contribute to self-supervised pre-training of large foundation models for 3D vision.
Train and specialise models for supervised tasks, including segmentation, classification and regression.
Keep up to date with the latest machine learning research and contribute to internal reading groups.
Contribute to the publication of high-impact conference, journal and sponsor-facing scientific outputs.
Write high-quality Python and PyTorch code for model training, inference and evaluation.
Translate model outputs into biomarkers that support clinical-trial endpoints, enrichment strategies and disease-characterisation workflows.
Work with clinical and scientific stakeholders to ensure model objectives are clinically meaningful.
Train large models across GPUs and compute nodes, working with ML Engineers to improve performance and scalability.
Work proactively, communicate progress clearly and identify risks early.

Requirements

Strong experience in machine learning research, with experience in either computer vision, foundation models, or 3D medical imaging.
Deep understanding of machine learning theory and its background, including deep learning, linear algebra, probability theory, statistics and optimisation.
Strong Python and PyTorch skills, with the ability to work confidently in model training and inference codebases.
Experience developing and evaluating deep learning models for imaging, segmentation, classification, regression or representation learning.
Experience with self-supervised learning, foundation models or large-scale model training.
Experience writing production-quality or research-to-production Python code.
Experience with modern software development workflows, including git, pull requests, code review, documentation and ticketing.
Strong communication skills and ability to work across ML, data science, clinical science and engineering teams.
Ability to be proactive, self-sufficient and rigorous when completing tasks.
Strong knowledge of Linux shells, git and modern Python development tools such as uv, poetry, ruff, black, mypy or ty.

Skills

Computer vision
Foundation models
3D medical imaging
Deep learning
Linear algebra
Probability theory
Statistics
Optimisation
Python
PyTorch
Segmentation
Classification
Regression
Representation learning
Self-supervised learning
Large-scale model training
Git
Linux shells

Location

Cambridge
London

Work Type

Full-time

Experience Level

Senior

Benefits

Annual bonus plan
Private medical insurance
Life insurance
Contributory pension scheme
25 days annual leave
Bank holidays
Enhanced maternity leave

About the Company

Qureight’s mission is to accelerate clinical trials and ensure breakthroughs in lung and heart disease reach patients without delay.
Our AI-powered data and imaging curation platform enables the analysis of clinical imaging and other healthcare data, helping our customers bring treatments to market, faster.
We’re looking for talented people who want their work to matter.
With offices in Cambridge and London, you’ll join our multidisciplinary team of clinicians, scientists, and engineers.
What unites us is our open culture, continuous learning mindset, and a shared mission to help biopharma run faster, smarter trials.

Equal Opportunity

Everyone is welcome at Qureight.
We are an equal opportunities employer and encourage applications from all suitably qualified candidates regardless of age, disability, ethnicity, sex, gender reassignment, religion or belief, sexual orientation, marriage and civil partnership, or pregnancy and maternity.
Women and other underrepresented groups may be less likely to apply for a role unless they meet all or nearly all of the requirements. If this applies to you, we still encourage you to apply – you may be a great fit, even if you don’t meet every qualification. We’d love to hear from you.
If you require any adjustments to the application or selection process, please let us know. We will be happy to support you.