PhD Journey
Hear our director share his inspiring journey into research and why he believes it’s for everyone.
Open Projects
MRI Without Boundaries: intelligent medical imaging for the playful child
PRoject no.: 2026_001
Supervisor 1: Jo Hajnal
Supervisor 2: Shaihan Malik
Supervisor 3: Tomoki Arrichi
RESEARCH DOMAINS: Breakthrough Technologies; Affordable and Accessible Imaging
INDUSTRY PARTNER: Siemens Healthineers
This PhD project aims to transform how Magnetic Resonance Imaging (MRI) is performed in young children by developing a completely new free-pose MRI capability. Conventional paediatric MRI relies on sedation because children struggle to remain still in the confined, noisy scanner, causing motion artefacts that degrade image quality. This project seeks to break that paradigm by building on four cutting-edge technologies:
1) A new ultra-wide-bore, low-field MRI scanner with light flexible receiver coils provides a spacious and safe environment where a child can adopt any comfortable posture.
2) In scanner interactive immersive technology creates a virtual world that engages the child and promotes natural stillness using eye-gaze control.
3) Real-time artificial intelligence (AI) to detect movement, estimate body pose, and dynamically update imaging geometry to maintain anatomical consistency.
4) Adaptive reconstruction algorithms to ensure high-resolution images despite motion or changing positions.
The project combines advances in biomedical engineering, AI, and human-machine interaction to deliver a technically transformative and socially impactful solution for paediatric MRI. By developing new software and methods you will create a system that continuously learns and adapts during scanning, enabling diagnostic-quality brain images without anaesthesia.
Agentic AI for Personalised and Clinical Task-Based PET Image Reconstruction
PRoject no.: 2026_002
Supervisor 1: Andrew Reader
Supervisor 2: Alexander Hammers
RESEARCH DOMAINS: Breakthrough Technologies; Precise Diagnosis and Prognosis
INDUSTRY PARTNER: Siemens Healthineers
Positron emission tomography (PET) is a powerful tool for studying the brain, but conventional image reconstruction methods use fixed algorithms and assumptions that cannot adapt to each patient’s unique data or clinical question.
This project introduces a new generation of intelligent PET image reconstruction using agentic artificial intelligence (AI): AI systems that can reason, adapt, and interact like human experts. Instead of applying one-size-fits-all settings, the AI will adjust the reconstruction process in real time, optimising parameters and priors based on the specific diagnostic task (for example, epilepsy or dementia) and even for different regions of the brain.
In the first year, the project will benchmark state-of-the-art methods, including advanced diffusion-based priors, to establish the best achievable image quality. In the second year, multiple cooperating AI agents will be developed to guide and refine reconstruction based on clinical intent, image content, and diagnostic feedback. By the third year, the system will evaluate its own reliability and uncertainty, producing confidence maps that show how trustworthy each part of the image is. This combination of agentic and generative AI aims to deliver clearer, more informative PET images tailored to each patient, supporting more accurate diagnoses and better clinical outcomes.
SELF-DRIVING FETAL MRI
PRoject no.: 2026_003
Supervisor 1: Shaihan Malik
Supervisor 2: Jana Hutter
Supervisor 3: Lisa Story
RESEARCH DOMAINS: Breakthrough Technologies; Precise Diagnosis and Prognosis
INDUSTRY PARTNER: Siemens Healthineers
Magnetic Resonance Imaging (MRI) provides exceptional insight into anatomy and development without using radiation. Each MRI examination consists of several sequences, each designed to capture different tissue contrasts or orientations. However, when the subject moves during acquisition, image quality degrades and sequences must often be repeated, extending scan time. This problem is particularly severe in fetal MRI, where fetal motion and maternal breathing cause frequent image artefacts, and where the unpredictable position of the fetus requires careful, manual planning by experienced operators.
Previous work demonstrated that artificial intelligence can enable the scanner to automatically track and follow the fetus in real time during MRI. This PhD project will extend that capability toward a self-driving fetal MRI examination, capable of autonomously planning and adapting the scan as it runs. The project will focus on developing methods for dynamic slice prescription, adaptive sequence control, and real-time adjustment of imaging parameters in response to motion and anatomy. By integrating these approaches into the scanner workflow, the system aims to acquire complete, high-quality data efficiently and reliably minimising operator input and improving both patient comfort and throughput.
New 99mTc and 188Re theranostic radiotracers for cancer treatment
PRoject no.: 2026_005
Supervisor 1: Michelle Ma
Supervisor 2: Gary Cook
Supervisor 3: Lefteris Livieratos
RESEARCH DOMAINS: Molecular Probes and Theranostics; Affordable and Accessible Imaging
INDUSTRY PARTNER: Serac Healthcare
This project aims to develop dual diagnostic imaging and injectable radiotherapeutic drugs for “hard-to-treat” cancers. It will apply synthetic, inorganic and radio chemistry, alongside in vitro and in vivo experiments including SPECT imaging, to identify new and efficacious radiotracers.
We have recently developed a versatile chelator platform to incorporate either diagnostic technetium-99m (Tc-99m) or radiotherapeutic rhenium-188 (Re-188) into cancer-targeting peptides or molecules (1), and demonstrated proof-of-principle by preparing a pair of Tc-99m and Re-188 radiotracers that target prostate cancer (2). This enables preparation of receptor-targeted, “theranostic” radiopharmaceuticals, for dual diagnostic imaging and systemic radiotherapy.
In this project, the student will select a biomolecule that targets a specific cell-surface receptor of a hard-to-treat cancer (pancreatic cancer, glioblastoma, ovarian cancer). The biomolecule will then be attached to our diphosphine chelator, and the resulting disphophine-biomolecule will be radiolabelled with Tc-99m and Re-188. The student will undertake in vitro and in vivo studies of the theranostic radiotracers, including biodistribution, SPECT imaging and therapeutic efficacy studies in a relevant mouse model of cancer.
This translational project would suit a student with a chemistry, pharmaceutical sciences or biochemistry background. The student will be supported by supervisors with expertise in chemistry, clinical cancer imaging, dosimetry and clinical translation of new radiotracers.
(1) Nuttall et al., Chem. Sci., 2025, 16, 17112. DOI: 10.1039/D5SC02110C.
(2) Pham et al., J. Nucl. Med., 2024, 65, 1087. DOI: 10.2967/jnumed.124.267450.
Development of Scandium-47 Theranostics from production to bedside
PRoject no.: 2026_006
Supervisor 1: Graeme Stasiuk
Supervisor 2: Steve Archibald
Supervisor 3: Lefteris Livieratos
Supervisor 4: Antonios Pouliopoulos
RESEARCH DOMAINS: Molecular Probes and Theranostics
INDUSTRY PARTNER: Astral Systems
Current clinical care of cancers relies on imaging of the tumour for diagnosis and therapeutic interventions (surgery, chemotherapy, radiotherapy) performed separately, sometimes several weeks apart. Critically, during this time, the tumour has the opportunity to grow and spread. In this project, we seek to combine both imaging and therapy into a match-paired theranostic treatment. This has the potential to inhibit tumour growth directly following diagnosis, by using the same intervention, i.e. with two different isotopes of the same element, one for imaging and one for therapy.
This project will utilise a “theranostic pair” in which two radionuclides of the same element are used (44/47Sc). This approach has the advantage of providing identical biological distribution between the imaging and therapy ensuring accurate diagnosis, dosimetry, and monitoring of disease progression. To do this we must improve the supply of the radionuclides, with this PhD opportunity focusing on the development of 47Sc for therapy and 44Sc for PET imaging, alongside the development of the targeting agent for brain tumours.
This project aims to develop 44/47Sc theranostics for brain tumours:
1) Developing methodology for production and purification of 47Sc
2) Developing 44/47Sc bioconjugate for glioma
3) Validate the theranostic of 44/47Sc in glioma models
Please check the opportunity below at the
School of Biomedical Engineering & Imaging Sciences.
Advancing Contrast-Enhanced Ultrasound for Functional Microvascular Assessment
APPLICATION DEADLINE: 24 May 2026 00:00
RESEARCH DOMAINS: Applied Physics, Medical / Biomedical Physics, Biomedical Engineering, Acoustics, Medical / Clinical Science, Applied Mathematics, Data Analysis
SEE DETAILS: Link to listing
There is an urgent clinical need for non-invasive methods to accurately assess the local environment and function in conditions such as sepsis. Such capability would enable improved monitoring of disease progression, support timely intervention, and ultimately improve patient outcomes.
This project aims to advance contrast-enhanced ultrasound by exploring and developing its ability to probe the environment, integrating principles from multiple state-of-the-art techniques, and new experimental approaches.
The specific objectives are:
To characterise microbubble signal responses to their local environment.
To develop methods to extract clinically relevant information from these signals.
To design and optimise acquisition pipelines to effectively exploit these signal characteristics.