PhD Studentship: Machine Learning Assisted Analysis in Placenta Pathology Work

The project:

When pregnancies encounter complications such as growth restriction, premature birth, or stillbirth, the placenta is reviewed by a specialist pathologist to determine the underlying causes. However, due to the limited number of specialists, delays in diagnosis are common, which can compromise care for mothers and future pregnancies. Traditionally, placenta pathology analysis involves the manual inspection of glass histopathology slides under magnification by pathologists. With the introduction of digital pathology, glass slides are replaced by digital scans, creating significant opportunities for the development of machine learning-assisted workflows.

With this in mind, the project aims to develop and evaluate trusted machine learning solutions that can pre-screen placenta pathology images for abnormalities and prioritise cases for pathologist review. Such AI-assisted pathology workflows promise to significantly reduce the perinatal pathology workload, enabling faster review of priority cases and guiding treatment to mitigate risks to both mother and baby in future pregnancies.

Working closely with leading clinicians from Great Ormond Street Hospital for Children, the design of the tools will be informed by a deep understanding of the clinical context, workflows, and needs of pathologists. This project offers an exciting opportunity to conduct cutting-edge machine learning research with the potential for real clinical impact.

How to apply:

Prior to submitting an online application, you will need to contact the project supervisor to discuss.

Online applications are made at http://www.bris.ac.uk/pg-howtoapply. Please select Computer Science on the Programme Choice page. You will be prompted to enter details of the studentship in the Funding and Research Details sections of the form.

Candidate requirements: 

Applicants must hold/achieve a minimum of a merit at master’s degree level (or international equivalent) in a science, mathematics or engineering discipline. Applicants without a master's qualification may be considered on an exceptional basis, provided they hold a first-class undergraduate degree. Please note, acceptance will also depend on evidence of readiness to pursue a research degree.

If English is not your first language, you need to meet this profile level: Profile E

Further information about English language requirements and profile levels.

Funding:

Minimum tax-free stipend at the current UKRI rate is £19,237 for 2024/25.

For eligibility and residence requirements please check the UKRI UK Research and Innovation website

Contacts:

For questions about the research topic, please contact: 

Professor Kenton O’Hara (kenton.ohara@bristol.ac.uk) or

Telmo de Menezes e Silva Filho (telmo.silvafilho@bristol.ac.uk)

For questions about eligibility and the application process please contact Engineering Postgraduate Research Admissions admissions-engpgr@bristol.ac.uk

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