Elsewhere on Ulster
This project is funded by:
Positioned within Ulster University’s School of Computing, this research theme advances cutting edge artificial intelligence and Internet of Things (IoT) solutions for healthcare and wellbeing.
The projects collectively address sectoral priorities in Life & Health Sciences and Software/Cyber, and are aligned with the Centre for Digital Healthcare Technology, part of the Belfast Regional City Deal.
Each PhD researcher will contribute to developing responsible, efficient, and trustworthy AI systems from cognitive fatigue management and personalised thermal comfort to multi modal medical imaging and IoT enabled healthcare.
The work aims to enhance patient safety, improve clinical decision making, and build public trust in emerging digital health technologies through secure, transparent, and ethical innovation.
Supervisor Names: Dr George Moore
Building on prior work detecting cognitive fatigue in mobile contexts, this opportunity addresses gaps highlighted in recent studies regarding low-burden, real-time support.
It investigates how passive sensing from smartphones and wearables can enable fatigue detection and trigger adaptive interventions. The methodology may involve interactive tasks simulating cognitively demanding contexts and collecting sensor data (Heart Rate Variability, touchscreen interactions, and mobility are collected).
Machine Learning models will be trained to infer fatigue in real time, triggering adaptive prompts, such as suggesting micro-breaks. Expected outcomes include a sensing pipeline, refined machine learning models, an intervention prototype, and insights into perceived user acceptability.
Supervisor Names: Dr Tazar Hussain
This PhD project investigates how Small or Lightweight Language Models (SLMs ) can enhance Internet of Things (IoT) applications, with a focus on healthcare.
The research aims to develop efficient, adaptive, and privacy-preserving AI systems capable of real-time reasoning on resource-limited devices. Key challenges include computational and energy constraints, latency, data privacy, and model interpretability in safety-critical environments.
The project’s objectives are to design lightweight, edge-deployable model architectures, optimize their reasoning and adaptability, and evaluate their performance in healthcare IoT use cases, ultimately enabling cost-effective, secure, and intelligent digital health solutions that improve patient monitoring and decision-making.
Supervisor Names: Dr Shengli Wu
This PhD project develops trustworthy multi-modal fusion networks for medical imaging, integrating complementary data from MRI, PET, CT, and histopathology to enhance diagnostic accuracy and clinical reliability.
It addresses key challenges of data heterogeneity, missing modalities, and interpretability by designing transformer- and attention-based fusion architectures with robust and explainable mechanisms.
Through benchmark validation and clinician-informed evaluation, the research aims to produce transparent, robust, and responsible AI systems that support safe, interpretable, and equitable decision-making in healthcare, advancing trustworthy AI applications in radiology, oncology, and neurology.
Supervisor Names: Dr Matias Garcia-Constantino
The effects of global warming have intensified in recent decades, with 2024 recording the highest global temperatures ever.
Heatwaves, extreme temperatures, and droughts pose serious health threats, particularly by increasing cardiovascular risks-the leading cause of death in the UK. Vulnerable populations, such as the elderly and those with preexisting conditions, face heightened danger from temperature fluctuations.
This PhD project aims to develop an IoT-based personalised Thermal Comfort model for Smart Homes that integrates biofeedback and sensors with Deep Learning to dynamically optimise indoor conditions. The goal is to reduce cardiovascular risks by linking thermal comfort to cardiovascular stability.
Applying to Multiple Projects: Applications for more than one PhD studentship are welcome, however if you apply for more than one PhD project within Computing, your first application on the system will be deemed your first-choice preference and further applications will be ordered based on the sequential time of submission.
If you are successfully shortlisted, you will be interviewed only on your first-choice application and ranked accordingly. Those ranked highest will be offered a PhD studentship.
In the situation where you are ranked highly and your first-choice project is already allocated to someone who was ranked higher than you, you may be offered your 2nd or 3rd choice project depending on the availability of this project.
The School of Computing at Ulster University holds Athena Swan Bronze Award since 2016 and is committed to promote and advance gender equality in Higher Education. We particularly welcome female applicants,as they are under represented within the school.
Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.
We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.
In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.
If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.
The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.
Appointment will be made on merit.
This project is funded by:
Our fully funded PhD scholarships will cover tuition fees and provide a maintenance allowance of £21,000 (approximately) per annum for three years* (subject to satisfactory academic performance). A Research Training Support Grant (RTSG) of £900 per annum is also available.
These scholarships, funded via the Department for the Economy (DfE), are open to applicants worldwide, regardless of residency or domicile.
Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.
*Part time PhD scholarships may be available to home candidates, based on 0.5 of the full time rate, and will require a six year registration period.
Due consideration should be given to financing your studies.
Submission deadline
Friday 27 February 2026
04:00PM
Interview Date
Mid April 2026
Preferred student start date
14 September 2026
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