PhD in Addressing Macular Diseases using Ultrathin Digital Optics

Location: Faculty of Engineering and Faculty of Science (Psychology), University of Nottingham, UK Start Date: October 2026 This PhD offers an opportunity to explore ultrathin metamaterials: a novel type of device that utilises digital and mathematical techniques to design multifunctional visual aids to help address and correct diseases of the eye. You will work at the intersection of mathematics, physics, AI, and clinical practice through careful design and production of optical metasurfaces, which can help to correct macular degeneration and other eyesight problems through careful control of light. Why apply for this PhD? Work on the next-generation optical physics using metamaterials Gain a unique combination of skills in mathematics, machine learning, photonics, and clinical practices in vision. Be part of a multidisciplinary research team spanning science and engineering, psychology, and healthcare. Access state-of-the-art laboratories and cleanroom facilities. Develop skills highly valued in both academia and industry. Project description Vision technology relies on careful use of optical components such as lenses. Undoubtedly, standard prescription lenses have been revolutionary in helping billions of people and their quality of life through helping to see more clearly. However, optical technologies are based on standard glass lenses and components which are bulky and have limited capabilities. Age-related macular degeneration (AMD) affects around 196 million people worldwide and is a leading cause of central vision loss. It reduces the ability to read, recognise faces, and perform everyday tasks, with limited treatment options available for most patients. Existing assistive technologies rely heavily on digital image processing or bulky external devices, which can be expensive, inconvenient, and inaccessible – where simple prescription lenses simply cannot address this. This project explores a new approach using optical metasurfaces —ultra-thin optical layers that shape light—to enhance vision directly, without electronics. The aim is to increase contrast at object edges, helping users distinguish shapes and details more clearly. While edge enhancement has been shown to improve visual performance in low-vision patients, it is currently achieved using digital systems. This PhD project translates the principle into a compact, passive optical solution. The project will combine: Mathematical modelling and simulation of optical/photonic structures and devices Fabrication of ultrathin metasurfaces using the University of Nottingham cleanrooms Clinical applications through visual neuroscience approaches Facilities and research environment: Photonics and visual neuroscience laboratories; Dedicated simulation and modelling softwares for electromagnetic and optical design; Access to dedicated cleanroom fabrication facilities; A collaborative research environment across psychology and engineering. Candidate profile Essential: 1. A 2:1 undergraduate degree or a Master’s degree in Physics, Applied Physics, Mathematical Sciences, Computer Science, Vision Science or a closely related subject from a recognised institution. 2. A background in at least one of the following: Photonics/Electromagnetics theory, design and simulations Nanoscience Visual neuroscience or opthalmology 3. Programming skills (Python, MATLAB, or similar) 4. Strong analytical and problem-solving skills. 5. Good written and spoken English. Desirable: Experience with photonic/electromagnetics simulation software. Familiarity with deep learning platforms (e.g. TensorFlow, PyTorch), Machine-learning mathematics and algorithms. Experience in Imaging systems (e.g. microscopy), and optical laboratory experiments (lasers/lenses) Funding/eligibility Open to UK, EU and international students who can provide their own funding capability. How to apply For any enquiries about the project, email Dr Mitchell Kenney at Mitchell.kenney@nottingham.ac.uk or Prof. Paul McGraw at paul.mcgraw@nottingham.ac.uk Shortlisted candidates will be invited for an interview