Novel optics and AI approaches to image the centre of a live root for the first time
This exciting opportunity is based within the thriving Optics and Photonics research group in Faculty of Engineering which conducts cutting edge research spanning exploration to translation, with curiosity driven projects all the way through to application in the clinic.
Vision
We are seeking a PhD student who is motivated, enthusiastic and keen to push the boundaries of what is currently possible when imaging with an optical microscope. Combing the latest in optical developments with the recent surge in AI, this project aims to image the centre of a live intact root for the first time - something not currently possible.
Motivation
This project will address a long-standing issue in plant biology: the inability to image the centre of live, intact plant roots. The ability to observe dynamic cellular processes at the centre of a live root for the first time will unlock entirely new lines of biological inquiry crucial for areas such as sustainable agriculture and food security. Such an imaging system would allow for studies of a plant’s resilience to drought, salinity, and water logging as well as responses to fungal infections and nanoparticle uptake. It is very common that new optical microscopy techniques are developed to image mammalian tissue, but these approaches are very slow to translate across to plant biosciences where the impact could be huge. As a result, exciting opportunities get missed.
When we use light to image deep into complex samples there is a common problem that occurs – the light gets distorted and scattered by the structures present in the sample. As a result, a nice quality focus and hence a nice image cannot be produced at depth into the sample. At Nottingham we have been working on this problem for several years and have developed methods that shape the incoming light with the equal but opposite distortion to that imposed by the sample to produce a high-quality image deep into the sample of interest. Recently we have been using AI and machine learning to predict the distortion present and significantly speed up this correction process.
This PhD project will take the latest in AI-informed wavefront correction techniques and tailor them to imaging deep into plant roots. It will use a range of state-of-the-art optical microscopes based in the Optics and Photonics research group, plus those housed in Plant Biosciences at the Sutton Bonnington campus. Data sets will be generated using simulated and experimental data and used to train networks to predict the common distortions that occur when imaging into plant roots. From here we can either correct for these distortions using the hardware in the microscope or in software using reconstruction algorithms. This is an exciting multidisciplinary PhD project that promises to make cutting-edge advances in all research areas involved..
Aim
This project combines practical hands-on optics experimentation with training neural networks to develop the next generation of optical microscopes. You will have the opportunity to gain skills in optical instrumentation and imaging, AI and machine learning, and plant biology and sample handling.
Your base will be in the Optics and Photonics group in the Faculty of Engineering. From here you will work with a team of academics and researchers across engineering, computer science and the biosciences.
You will be supervised by:
- Dr Amanda Wright - Optics and Photonics research group, Faculty of Engineering
- Professor Mike Somekh - Optics and Photonics research group, Faculty of Engineering
- Dr Mike Pound - Computer Vision, Computer Science Department
- Dr Darren Wells - Plant and Crop Biophysics, School of Biosciences
Candidate requirements
An enthusiastic, self-motivated, resourceful student who likes working as part of a team and is keen to take on a new challenge. An understanding of optics and/or machine learning is desirable but not essential, along with general coding skills. 1st or a 2:1 in a relevant field, for example physics, electrical and electronic engineering, computer science, or biosciences.
Eligibility and funding
This studentship is open to UK/home and international candidates.
After a suitable candidate is found, funding is sought from the University of Nottingham as part of a competitive process. This will cover home tuition fees and UKRI stipend.
PhD start date: October 2026
How to apply
Application deadline: 9 March 2026
To apply, please email your CV and supporting statement to Amanda Wright at amanda.wright@nottingham.ac.uk
The University of Nottingham actively supports equality, diversity and inclusion and encourages applications from all sections of society. We - the Faculty of Engineering - provide a thriving working environment for all our postgraduate researchers (PGRs) creating a strong sense of community across research disciplines. We understand that research culture is important to our PGRs so we work closely with our Postgraduate Engineering Society and PGR research group representatives to support and enhance the postgraduate research environment.
As a PGR at the University of Nottingham you will benefit from training through our Researcher Academy’s training programme. Based within the Faculty of Engineering you will have additional access to courses developed specifically for our engineering and architecture PGRs including sessions on how to write a paper, communicating your research, and research integrity.
We offer dedicated postgraduate study spaces, have outstanding research facilities and work in partnership with leading industrial partners.