AI Scientist – AI for Medical Imaging

JR United Kingdom; Cambridge; On-site; GBP 50,000 - 60,000; Full time

Job summary

A leading company in AI-driven medical diagnostics is seeking an AI Scientist for a 6-month position focused on developing interpretable AI algorithms for medical imaging. The role involves collaboration with clinical teams and offers a unique opportunity to work with large-scale medical datasets, contributing to innovative research and publications.

Qualifications

• Master’s or PhD in a related field or equivalent experience.
• Experience in image classification and segmentation tasks.
• Track record of publications in relevant conferences or journals.

Responsibilities

• Design and implement machine learning models for analyzing biopsy images.
• Collaborate with clinical teams to ensure algorithm relevance.
• Contribute to experimental design and model evaluation.

Skills

Python

PyTorch

Machine Learning

Data Science

Education

Master’s or PhD in a related field

Tools

NumPy

Pandas

Matplotlib

SciPy

Job description

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AI Scientist – AI for Medical Imaging, Cambridge

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Client:

Location:

Cambridge, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

2

Posted:

23.05.2025

Expiry Date:

07.07.2025

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Job Description:

AI Scientist – AI for Medical Imaging

Duration: 6 months

Start Date: Summer 2025

Salary: £50,000-£60,000 pro rata (based on experience)

About Us

Lyzeum Ltd is a University of Cambridge spin-out at the forefront of AI-driven medical diagnostics. Building on our recent publication in NEJM AI (https://bit.ly/nejm-ai) and coverage in national media (https://bit.ly/guardian-coeliac), we are pioneering interpretable artificial intelligence algorithms for the diagnosis of small intestinal biopsies. We are nearing clinical trial readiness, with the potential for regulatory approval and clinical deployment.

We are seeking a highly motivated AI scientist to join our team for a 6-month position. As part of the role, you will receive a visiting affiliation with the University of Cambridge and work on-site at Addenbrooke’s Hospital at least two days per week, with flexibility for hybrid working.

Role Overview

You will contribute to the development and refinement of interpretable AI algorithms focused on classification and segmentation tasks. Building on our work in coeliac disease detection, you will help expand our models models to other small intestinal conditions. With access to the world’s largest collection of digitised small intestinal biopsies, you’ll have a unique opportunity to develop and evaluate cutting-edge algorithms at scale.

Key Responsibilities

• Design and implement machine learning models for the analysis of scanned small-intestinal biopsy images

• Collaborate closely with clinical and technical teams to ensure clinical relevance and interpretability of the algorithms

• Contribute to experimental design, model evaluation, and documentation

• Co-author papers for submission to high-impact medical journals.

• Strong proficiency in Python and PyTorch

• Ability to work independently and collaboratively in multidisciplinary teams

Desirable Qualifications

• Master’s or PhD in a related field or equivalent experience

• Experience in image classification, instance segmentation, and semantic segmentation tasks

• A track record of publications in machine learning or medical imaging conferences or journals

• Experience working with large-scale medical datasets

• Experience contributing to open-source GitHub projects and strong proficiency in Python-based data science tools (e.g., NumPy, Pandas, Matplotlib, SciPy)

How to Apply

To apply, please email your CV and a brief cover letter (up to 500 words) outlining your relevant experience and motivation for joining Lyzeum Ltd to [emailprotected] . The closing date is 16 June 2025; however, applications will be reviewed on a rolling basis, so early applications are encouraged.

Lyzeum Ltd is committed to building an inclusive team. If you require any adjustments at any stage of the application process, please don't hesitate to contact us at [emailprotected] .