PhD Studentship: Developing and validating 3D-OCT-based tools for posterior eye shape characterisation

Developing and validating 3D-OCT-based tools for posterior eye shape characterisation

Applications are invited for a fully funded three-year PhD studentship sponsored by Carl Zeiss AG. The studentship will start on 1 October 2026; applications are also welcome for a 1 January 2027 start.

DoS: Dr Daniela Oehring, (daniela.oehring@plymouth.ac.uk)

2nd Supervisor: Mr Adam Kyte

3rd Supervisor: Prof. Mona Nasser

4th Supervisor: Dr Dena Bazazian

5th Supervisor: Prof. Ahmed Elsheikh (University of Liverpool)

Project Description

This fully funded PhD studentship will develop and validate 3D-OCT-based tools for characterising the shape of the posterior eye. Traditional ocular biometry focuses on axial length, corneal curvature and anterior chamber depth, yet the shape of the posterior eye – the retina and underlying sclera – carries critical diagnostic and prognostic information. Recent advances in Optical Coherence Tomography (OCT) now make it possible to capture detailed, in vivo representations of posterior curvature.

The project will establish optimised OCT acquisition and de-warping methods, build robust segmentation and curvature-analysis algorithms, and validate clinically meaningful shape metrics in ex vivo and in vivo studies. Applications span myopia progression, glaucoma, macular degeneration and surgical planning (including intraocular lens selection and laser refractive procedures).

Working in the Faculty of Health and in partnership with Carl Zeiss AG and the ZEISS Innovation Hub, the successful candidate will gain interdisciplinary training spanning clinical vision science, biomedical engineering, advanced image processing and machine learning. The studentship suits a candidate with a strong background in optometry, physics, engineering, computer science or a related discipline, and an interest in translational medical-device research.

The work is structured in three phases: protocol development and ex vivo validation; algorithm refinement and an in vivo pilot; and clinical application, including a methodology for a normative database of posterior-shape metrics.

Eligibility

Applicants should have a first or upper second-class honours degree in an appropriate subject or a relevant Master’s qualification.  

This is a highly interdisciplinary PhD project at the interface of biomedical engineering, imaging science, and clinical ophthalmology. The ideal candidate will have a strong background in engineering or computational sciences, with a keen interest in medical imaging, translational vision research, and healthcare innovation. They will join a dynamic supervisory team with strong academic and industrial links, including Carl Zeiss AG, working on cutting-edge challenges in ocular biometry and personalised diagnostics.

Essential criteria

• A first-class or upper second-class degree (or international equivalent) in one of: Software Engineering; Biomedical Engineering; Electrical/Optical Engineering; Mechanical Engineering; or Computer Science with a focus on imaging or applied data science.
• Demonstrated experience in one or more of: medical or optical imaging (e.g. OCT, MRI, CT); image processing and analysis of 2D/3D data; computational modelling, simulation, or optical system design.
• Proficiency in programming for data analysis and algorithm development (e.g. Python, MATLAB).
• Strong analytical skills and the ability to critically evaluate technical and scientific literature.
• Excellent communication skills and willingness to work in a cross-disciplinary, collaborative environment.

Desirable criteria

• Experience with machine learning or pattern recognition methods.
• Familiarity with wavefront sensing, ray tracing, or digital eye modelling.
• Exposure to medical device development or regulatory research environments.
• Understanding of clinical study design or experience working with human or animal data.
• Knowledge of ocular anatomy, vision science, or translational healthcare applications.

For Funding Details and How to Apply, please click the Apply button above.

The closing date for applications on 20/08/2026.