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IMany long-term studies rely on repeated eye scans, using Optical Coherence Tomography (OCT), to understand how vision changes as people get older. Traditionally, these scans are taken using large, stationary machines in specialist clinics. While effective, this approach can be inconvenient and sometimes impractical for older adults, people with limited mobility, or those who need frequent follow-up appointments. Handheld OCT scanners offer a more flexible alternative. They can be used in a wider range of settings and make it easier to collect scans from people who might otherwise struggle to attend regular clinic visits. However, because these devices are portable, the images they produce can vary in quality, making it difficult to compare scans reliably over time. The main focus of my work is to assess whether handheld scanning is truly feasible for long-term studies, and whether it can provide information that is consistent enough to be trusted. To do this, I create and use artificial intelligence models as a practical tool to analyse large numbers of scans in a consistent way. This allows subtle changes to be tracked over time, even when images are not perfectly captured. The aim is not to replace clinicians, but to understand whether handheld scanning, supported by intelligent analysis, can reduce barriers to participation, improve follow-up rates, and make long-term eye monitoring more inclusive. If successful, this approach could help reshape how eye health studies are carried out in ageing populations, making them more flexible, scalable, and patient-friendly.

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My PhD explores whether advanced retinal imaging can act as a non-invasive window into the brain to improve understanding and monitoring of neurodegenerative diseases, specifically Multiple Sclerosis and Alzheimer’s disease. Because the retina is part of the central nervous system, changes in its structure and microvasculature may reflect underlying brain pathology. Using multimodal imaging techniques across well-characterised clinical cohorts, I investigate whether retinal biomarkers can provide accessible, clinically meaningful tools for tracking disease progression and supporting earlier intervention.

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To trial the potential of several novel or understudied controls for the management of populations of cyanobacteria and zebra mussels, with a future potential implementation as part of reservoir management for harmful aquatic species.

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This study aims to explore the experiences of people diagnosed with pancreatic cancer in Northern Ireland and develop a theory to explain the process of their journeys from (pre)diagnosis to survivorship or to end of life. This deeper understanding will help to inform priorities for future research, support interventions, policy, and services.

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I am using novel thermal imaging technologies to carry out density estimation of badgers, comparing new and traditional methods of non-invasively monitoring such nocturnal populations.

Contact Emily here.

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This project aims to identify multiomic signatures associated with cardiometabolic syndrome in an aging population. Age-related diseases, such as metabolic syndrome, increase in prevalence as populations get older and costs the NHS over £6 billion annually. There is an urgent need to identify biomarkers that predict health and disease across the lifecourse, with a focus on enabling identification of those most at risk of disease development. This project merges demographic, clinical and biological datasets with MultiOmic Health’s expertise in applying novel AI techniques, to address a significant unmet need and public health priority.

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My PhD is exploring how stem cells and their secreted nanoparticles, extracellular vesicles, can alter the immune response in the autoimmune disease, systemic lupus erythematosus.

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This project will focus on identifying biomarkers to stratify Barrett’s oesophagus patient’s risk of developing oesophageal adenocarcinoma. It will utilise numerous techniques to determine morphological and molecular features which are associated with disease progression. These will include artificial intelligence and genomic sequencing analysis techniques. Identification of novel morphometric or transcriptomic signatures will provide improved surveillance strategies for Barret’s patients including targeted interventions for high-risk individuals and a reduction of unnecessary procedures for those considered low risk.

Contact Richard via email here.

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This research seeks to understand how training can support the delivery of oral healthcare in supported living settings. It will involve stakeholders across the sector to establish strategies for successful delivery and implementation of training interventions.

Contact Patrick via email here.

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The Concussion Understanding Training in Education (CUTE) Project is a mixed-methods project. Stage 1: interviews to explore the lived experiences of children and young people who have sustained a concussion. Stage 2: a pilot randomised controlled trial testing Brain 101, a concussion education resource developed in USA, for use in schools in Northern Ireland.

Contact Olivia via email here.

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My PhD project investigates the potential human health effects of exposure to micro- and nanoplastics of varying polymer types and particle sizes, alongside two selected pesticides. Human cell culture models are used to examine cellular and molecular responses following controlled exposure to these contaminants. Analytical chemistry and RNA sequencing are used to identify metabolic and gene expression changes, with the aim of improving understanding of toxicological mechanisms relevant to human health.

Contact Orlagh via email here.

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The project aims to find a natural, ideally seaweed-based feed additive which reduces the enteric methane emissions of ruminants (cattle and sheep). Primary aims include reducing methane emissions by ~20% whilst maintaining the productivity and wellbeing of the animal.

Contact Ben via email here.

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This PhD study aims to explore the psychosocial experiences of adolescents who have had a parent diagnosed with pancreatic cancer. Following a systematic review of the existing research, we intend to interview young people aged 10-24 years in the UK who experienced their parent's pancreatic cancer diagnosis during their adolescent years. We will also interview their parents, who can provide an additional perspective of this phenomenon. Beyond documenting and analysing their experiences, this PhD will involve the use of a participatory approach, the World Café, which will bring young people, families, healthcare professionals, and support organisations together to share experiences and identify potential solutions for improving psychosocial support. This research will provide in-depth insights into what it really means to be a young person when your parent has pancreatic cancer. By understanding these experiences, we aim to better inform solutions that could ease their journey through a challenging time.

Contact Caitlin via email here.

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My project's aim is to control invasive terrestrial plant species using novel techniques in an attempt to find alternatives to glyphosate herbicide.

Contact Christopher via email here.

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Development and testing of a proof-of-concept Cathepsin S ProteaseTag Activity-Based Immunoassay

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Ocular inflammation, including uveitis, postoperative inflammation, and allergic conjunctivitis, is commonly treated using topical corticosteroid eye drops. However, conventional eye drops suffer from extremely low ocular bioavailability (typically less than 5%) due to rapid tear turnover, limited corneal permeability, and nasolacrimal drainage. These limitations necessitate frequent dosing, reduce therapeutic efficacy, and may increase the risk of systemic absorption and steroid-related side effects. To overcome these challenges, this project proposes the development of a novel nanotechnology-based ocular patch designed to enhance drug bioavailability, prolong retention time, and provide controlled release of anti-inflammatory corticosteroids.

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