Machine learning for imaging analysis in large bowel diagnostics

We are thrilled to announce an exciting opportunity to join our cutting-edge research team at the Endorobotics Lab, led by Dr. Luigi Manfredi, in collaboration with the School of Medicine and the School of Science and Engineering at the University of Dundee. This project aims to advance machine learning (ML) techniques for imaging analysis in large bowel diagnostics, focusing on polyp detection and the characterization of inflammatory bowel diseases (IBD).

Colorectal cancer screening and IBD diagnosis are critical for improving patient outcomes, yet existing imaging methods often require significant operator expertise and suffer from variability in accuracy. The project will address these challenges by leveraging state-of-the-art ML algorithms to enhance image-based diagnostic capabilities.

The student will work on designing and implementing advanced ML models, such as deep learning architectures, to process and analyse high-resolution endoscopic images. Objectives include developing systems for automated polyp detection, differentiation of neoplastic from non-neoplastic lesions, and classification of IBD phenotypes. These tools will be trained and validated using datasets obtained through collaborations with clinical partners and training centres.

In addition to algorithm development, the project will explore real-time integration of ML tools into flexible endoscopy systems, enabling immediate feedback to clinicians during procedures. The outcomes will aim to reduce diagnostic variability, enhance accuracy, and improve clinical decision-making.

The project will be hosted at the University of Dundee, with access to the Centre for Medical Engineering and Technology (CMET) and advanced computational resources, fostering a collaborative and innovative research environment.

Desired skills and qualifications

We are seeking a candidate with:

• Strong programming skills (e.g., Python, TensorFlow, or PyTorch).
• A degree in Computer Science, Machine Learning, Biomedical Engineering, or a related field.
• A keen interest in medical imaging and AI-based diagnostics.
• Experience in deep learning or computer vision is desirable but not mandatory.

What we offer

• An opportunity to work in a vibrant, multidisciplinary research environment.
• Access to state-of-the-art imaging and computational facilities.
• Mentorship from leading experts in medical devices and machine learning.
• A chance to contribute to impactful research improving diagnostic accuracy and patient care.

Diversity statement

Our research community thrives on the diversity of students and staff which helps to make the University of Dundee a UK university of choice for postgraduate research. We welcome applications from all talented individuals and are committed to widening access to those who have the ability and potential to benefit from higher education.

There is no funding attached to this project.  The successful applicant will be expected to provide the funding for tuition fees and living expenses, via external sponsorship or self-funding.