Projects for October 2026 will be advertised at the end of November.
The ones listed below are from our 2025 round.
2025_01: From Multimodality to Insight - Beyond GenAI in Medicine
Supervisors:
Dr Zina Ibrahim
Project themes:
1.AI, Machine Learning, and Multimodal Data
2. Neuroscience and Mental Health
3. Imaging
2025_02: Towards Trustable Healthcare Generative AI Models
Supervisors:
Dr Zina Ibrahim
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_03: ADHD transition: using remote technology to identify targets for intervention
Supervisors:
Dr Jonna Kuntsi, Professor Richard Dobson
Project themes:
1.Omics and Bioinformatics
2.AI, Machine Learning, Multimodal Data
2025_04: Sexual minority group membership: Classification and the prediction of common mental health problems
Supervisors:
Dr Qazi Rahman
Project themes:
1.Omics and Bioinformatics
2.AI, Machine Learning, and Multimodal Data
2025_05: Explainable AI for medical image classification: applications to brain imaging
Supervisors:
Professor Hana Chockler
Project themes:
1.Omics and Bioinformatics
2.AI, Machine Learning, and Multimodal Data
2025_06: Explainable AI for Accelerometer Data To Detect Neurological Deterioration in Cancer Patients
Supervisors:
Professor Hana Chockler
Project themes:
1.Omics and Bioinformatics
2.AI, Machine Learning, and Multimodal Data
2025_07: Developing and applying novel propensity scoring approaches for target trial emulations using electronic health records (EHRs)
Supervisors:
Professor Sabine Landau, Dr Giouliana Kadra
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Neuroscience and Mental Health
2025_08: Developing synthetic control methods to utilise patient timelines generated by the Foresight transformer for target trial emulations using electronic health records (EHRs)
Supervisors:
Professor Sabine Landau, Dr Nilesh Pareek
Project themes:
1.Omics and Bioinformatics
2.AI, Machine Learning, and Multimodal Data
2025_09: Co-designing a virtual reality mindfulness application with people with diabetes to reduce diabetes distress and improve quality of life
Supervisors:
Dr Siobhan O'Connor, Professor Wei Liu
Project themes:
1.Omics and Bioinformatics
2025_10: Multiomics analysis of aging heart
Supervisors:
Dr Maxim Freydin, Dr Pier Giorgio Masci
Project themes:
1.AI, Machine Learning, and Multimodal Data
2. Imaging
3. Neuroscience and Mental Health
2025_11: When are large language models (LLMs) good enough for health care? SOLACE-AI
Supervisors:
Dr Iain Marshall, Dr Martin Chapman
Project themes:
1. EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3. Mobile Health and other patient generated/non-healthcare data
2025_12: Pulse oximetry in pregnancy
Supervisors:
Professor Peter von Dadelszen, Professor Laura McGee
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_13: Development and deployment of a single unified natural language model for the supervised and automated prediction of follow up for precancerous GI conditions
Supervisors:
Dr Sebastian Zeki, Dr Angus Roberts
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3. Neuroscience and Mental Health
2025_14: Early detection of cardiac arrhythmia risks from ECG using AI and cardiac digital twins to uncover the underlying cardiomyopathy
Supervisors:
Professor Oleg Aslanidi, Professor Pablo Lamata
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_15: Advancing Cardiovascular Disease Diagnosis and Medical Report Generation Through Deep Generative Models
Supervisors:
Dr Lei Lu
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Imaging
2025_16: In silico identification of potent noncoding neoantigens for cancer vaccine development
Supervisors:
Dr Mohammad Mahdi Karimi, Dr Sheeba Irshad
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_17: Towards finding clinical and immunological signatures from a heterogeneous and multimodal clonal haematopoiesis data
Supervisors:
Dr Mohammad Mahdi Karimi, Dr Giorgio Napolitani
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Mobile Health and other patient generated/non-healthcare data
2025_18: Personalised IoT data-based health and performance systems for safe and sustainable future human spaceflight
Supervisors:
Dr Peter Hodkinson, Professor Yang Gao
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3. Neuroscience and Mental Health
2025_19: Advanced statistical methods for multimodal bioimages in cancer research
Supervisors:
Dr David Pigoli, Professor Maddy Parsons
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_20: Developing an AI-informed risk prediction model of the relationship between suicide, comorbidity, medication, and gambling-related suicide risk: A comparative study between Armed Forces and civilian populations
Supervisors:
Dr Daniel Leightley, Dr Alex Dregan
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
3.Neuroscience and Mental Health
2025_21: Evaluating pharmacological approaches to management of pregnancy complications using the ‘Born in South London’ (eLIXIR) data linkage; a study of metformin treatment
Supervisors:
Dr Sara White, Professor Lucilla Poston
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Neuroscience and Mental Health
2025_22: Combining maternal wearables and clinical data to detect abnormal fetal growth; a study in pregnant women
Supervisors:
Dr Sara White, Dr Michele Orini
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Neuroscience and Mental Health
2025_23: Leveraging AI and Large Language Models to Develop a Patient Narrative Dashboard
Supervisors:
Dr Ben Holgate, Dr Angus Roberts
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
2025_24: Exploring the relationship between mental health and musculoskeletal injuries in Serving Armed Forces personnel: A mixed methods study to develop an AI-powered risk prediction framework
Supervisors:
Dr Daniel Leightley, Dr Katie Dalrymple
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Neuroscience and Mental Health
4.Mobile Health and other patient generated/non-healthcare data
2025_25: Predicting ADHD: AI-Driven Prognostic Tools for Symptom Trajectory and Outcome
Supervisors:
Dr Gustavo Sudre, Philip Shaw
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
3.Neuroscience and Mental Health
2025_26: New language modeling approaches to tackle climate-health emergencies - SOLACE-AI
Supervisors:
Dr Iain Marshall
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_27: Integrating EEG, MRI, and routine health records to understand epileptogenesis from perinatal risk factors to childhood phenotypes
Supervisors:
Dr Kimberley Whitehead, Professor Jonathan O'Muircheartaigh
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Neuroscience and Mental Health
2025_28: Individualised prediction models for preterm infants which leverage the 'bumpiness' of their clinical course using high temporal resolution routine health data
Supervisors:
Dr Kimberley Whitehead, Dr Raquel Iniesta
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Neuroscience and Mental Health
2025_29: Towards a digital twin of the fetal heart: Predicting coarctation of aorta
Supervisors:
Dr Maria Deprez, Professor Pablo Lamata
Project themes:
1.Omics and Bioinformatics
2.AI, Machine Learning, and Multimodal Data
3.Imaging
4.Neuroscience and Mental Health
2025_30: Design of a modular probabilistic expert system based on Object-Oriented Bayesian Networks to facilitate the interpretation and collation of toxicological findings
Supervisors:
Dr Matteo Gallidabino, Dr Vincenzo Abbate
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
3.Neuroscience and Mental Health
2025_31: Harnessing multiomics and deep clinical phenotyping to develop predictive models for preterm birth
Supervisors:
Professor Rachel Tribe, Dr Alessandra Vigilante
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
3.Neuroscience and Mental Health
4.Mobile Health and other patient generated/non-healthcare data
2025_32: Integration of epigenetic profile in MND clinical trials design
Supervisors:
Dr Ahmad Al Khleifat, Dr Sarah Marzi
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_33: Optimizing Clinical Trials in Motor Neuron Disease: Harnessing Immune Biomarkers and Machine Learning for Predicting Disease Progression
Supervisors:
Dr Ahmad Al Khleifat, Dr Ammar Al-Chalabi
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_34: PrognostiOmics: Multiomics Scores for Predicting Age of Onset in ALS
Supervisors:
Dr Ahmad Al Khleifat, Dr Oliver Pain
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_35: The role of mitochondria in the causal pathways of neurodegenerative disorders
Supervisors:
Dr Alan Hodgkinson, Dr Alfredo Iacoangeli
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
3.Neuroscience and Mental Health
2025_36: Understanding the heart-brain connection to tackle dementia and cardiovascular diseases using deep learning generative, advanced statistical and genetic modelling
Supervisors:
Professor Alistair Young, Pier-Giorgio Masci
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_37: Clinical Trial Patient Matching with Multimodal Learning
Supervisors:
Dr Angus Roberts, Dr Tao Wang
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Neuroscience and Mental Health
2025_38: Modeling Multimorbidity Trajectories in Individuals with Severe Mental Illness Using Graph Reinforcement Learning
Supervisors:
Dr Angus Roberts, Dr Tao Wang
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
3.Neuroscience and Mental Health
2025_39: Developing a digital twin model to simulate the brain’s response to EEG-based neurofeedback– a potential neurorehabilitation approach for childhood dystonia/dystonic cerebral palsy
Supervisors:
Dr Crina Grosnan, Dr Verity McClelland
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
2025_40: Dynamic Statistical Learning Models for Real-time Prediction and Monitoring Patient Outcomes at Scale
Supervisors:
Dr Ewan Carr, Professor Kimberley Goldsmith
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_41: Clinical portable ultra-low-field neuroimaging
Supervisors:
Dr František Váša, Dr Thomas Booth
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Neuroscience and Mental Health
2025_42: Data-driven Neurorehabilitation
Supervisors:
Professor James Teo
Project themes:
1.Omics and Bioinformatics
2.EHRs, NLP, and LLMs
3.AI, Machine Learning, and Multimodal Data
2025_43: Data-driven Dementia Treatment Adoption
Supervisors:
Professor James Teo
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Mobile Health and other patient generated/non-healthcare data
2025_44: Data-driven treatments of Multiple Sclerosis and Neuroinflammation
Supervisors:
Professor James Teo, Dr Arman Eshagi
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_45: Evaluating the Impact of Fortification of Non-Wholemeal Wheat Flour with Folic Acid on Maternal-Fetal and Child Outcomes in UK Mother-Child Cohorts
Supervisors:
Dr Kathryn Dalrymple, Professor Lucilla Poston
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_46: Assessing the impact of medicines and supplements used in pregnancy on maternal and infant outcomes using the eLIXIR-Born in South London Data Linkage Cohort
Supervisors:
Dr Kathryn Dalrymple, Professor Laura Magee
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_47: Leveraging Machine Learning for High-Dimensional Mediation: Explaining Outcomes of Psychological Therapy for Anxiety and Depression
Supervisors:
Professor Kimberley Goldsmith, Dr Ewan Carr
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_48: Interrogating smooth muscle cell heterogeneity in vascular ageing and disease using an integrated workflow for scRNAseq
Supervisors:
Dr Konstantinos Theofilatos, Professor Catherine Shanahan
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_49: Deep Phenotyping of Heatwave Resilience in Older Adults
Supervisors:
Dr Mary Ni Lochlainn, Professor Claire Steves
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Imaging
2025_50: Exploiting Fabric-Based Sensor Technology for Human Activity Recognition in Healthcare
Supervisors:
Dr Matthew Howard, Dr Irene Di Giulio
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Imaging
2025_51: Computer vision-based control system for a novel of myoelectric prosthetic to improve reliability and user experience
Supervisors:
Dr Nicola Bailey, Dr Letizia Gionfrida
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Neuroscience and Mental Health
4.Mobile Health and other patient generated/non-healthcare data
2025_52: Causal artificial intelligence to improve obesity treatment
Supervisors:
Dr Oliver Canfell, Dr Nicola Paoletti
Project themes:
1.Omics and Bioinformatics
2.EHRs, NLP, and LLMs
3.AI, Machine Learning, and Multimodal Data
4.Imaging
5.Neuroscience and Mental Health
2025_53: Digital transformation of multidisciplinary weight management services in South-East London
Supervisors:
Dr Oliver Canfell, Dr Alastair Duncan
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_54: Machine learning based assessment of masses of the heart using Cardiac MRI to enhance patient diagnosis and management
Supervisors:
Dr Sohaib Nazir, Professor Andrew King
Project themes:
1.Omics and Bioinformatics
2.AI, Machine Learning, and Multimodal Data
2025_55: Technologies for Enabling Fairness and Access in Co-Design
Supervisors:
Dr Timothy Neate
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_56: Enabling Health Data Equity through Accessible Patient Portals
Supervisors:
Dr Timothy Neate, Dr Martin Chapman
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
2025_57: Differential geometry for explaining and simulating cellular processes
Supervisors:
Professor Anita Grigoriadis, Dr Christopher Banerji
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Neuroscience and Mental Health
2025_58: Natural Language Processing for diagnosis and enhanced risk stratification in Inherited Cardiovascular Conditions
Supervisors:
Dr Antonio de Marvao, Professor James Teo
Project themes:
1.Omics and Bioinformatics
2.AI, Machine Learning, and Multimodal Data
2025_59: AI-ECG and natural language processing for large scale Inherited Cardiac Conditions diagnosis and risk stratification
Supervisors:
Dr Antonio de Marvao, Professor James Teo
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_60: Leveraging Electronic Health Records and Genetic Data for Personalized Antidepressant Treatment: A Causal Analysis Approach
Supervisors:
Professor Cathryn Lewis, Dr Angus Roberts
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_61: Unlocking the potential of wearable monitoring in the elderly: prediction of adverse events and cognitive decline
Supervisors:
Dr Michele Orini, Dr Amos Folarin
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Mobile Health and other patient generated/non-healthcare data
2025_62: Causal modelling and explainable deep learning to disentangle the roles of iron imbalance, neuroinflammation and demyelination in Alzheimer’s Disease through quantitative magnetic resonance imaging
Supervisors:
Dr Po-Wah So, Dr Maria Deprez
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
3.Neuroscience and Mental Health
2025_63: Modelling cognitive, mental health and functional outcomes after traumatic brain injury using automated digital assessment technology
Supervisors:
Professor Adam Hampshire, Dr Aminul Ahmed
Project themes:
1.Omics and Bioinformatics
2.AI, Machine Learning, and Multimodal Data
3.Imaging
2025_64: ALS in a Global Context: Integrating Genomic and Epigenomic Data from Diverse Populations
Supervisors:
Dr Ahmad Al Khleifat, Dr Sarah Marzi
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_65: Using functional genomics to investigate genetic correlation across human diseases and to unravel the underlying biological mechanisms
Supervisors:
Dr Alfredo Iacoangeli, Dr Oliver Pain
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Neuroscience and Mental Health
3.Mobile Health and other patient generated/non-healthcare data
2025_66: Investigating the functional role of human endogenous retroviruses using lond-read sequencing
Supervisors:
Dr Alfredo Iacoangeli, Professor Gerome Breen
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Omics and Bioinformatics
2025_67: Systematic assimilation of routinely collected clinical data for risk stratification and outcome prediction in liver transplantation
Supervisors:
Dr Chris Callaghan, Professor James Teo
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_68: Longitudinal familial kinship and genetic analyses in the Genetic Links to Anxiety and Depression and UK BioBank studies
Supervisors:
Professor Gerome Breen, Dr Moritz Herle
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Neuroscience and Mental Health
2025_69: Developing and testing of a novel natural language processing algorithm to identify recovery in mental health electronic records
Supervisors:
Dr Giouliana Kadra-Scalzo, Dr Angus Roberts
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Neuroscience and Mental Health
2025_70: A Unified Transformer-Based Natural Language Processing Framework for Electronic Health Records
Supervisors:
Dr Jack Wu, Dr Thomas Searle
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_71: Using genetic biobank data to identify common factors between placental function and cardiovascular disorders
Supervisors:
Dr Jennifer Frost, Professor Rebecca Oakey
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_72: Feasibility of a large language model-powered health coach integrated with wearable data for lifestyle modifications in young adults
Supervisors:
Professor Josip Car
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_73: Synthesising Realistic Patient Timelines Using LLMs for Counterfactual Modelling in Dynamic, Time-Varying Treatment Regimes
Supervisors:
Associate Professor Julia Ive, Professor Richard Dobson
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_74: Streamlining Access to Clinical Guidelines with Knowledge-Infused LLMs
Supervisors:
Associate Professor Julia Ive, Professor Richard Dobson
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Imaging
4.Neuroscience and Mental Health
2025_75: Using online gamified testing to identify early psychosis
Supervisors:
Dr Kelly Diederen, Dr Thomas Spencer
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_76: Using Artificial Intelligence Methods to improve the representative nature of Clinical Trial Populations
Supervisors:
Dr Kevin O'Gallagher, Professor Richard Dobson
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_77: iHFpEF: AI imaging analysis of echocardiographic data to allow development of a fully integrated prediction model for heart failure with preserved ejection fraction (HFpEF) using both echo and clinical data
Supervisors:
Dr Kevin O'Gallagher, Professor Alistair Young
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_78: A multimodal data-driven approach to sustainable healthcare - leveraging community volunteering support to improve patients’ mental health outcomes
Supervisors:
Dr Mariana Pinto da Costa, Professor Robert Stewart
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
3.Neuroscience and Mental Health
2025_79: Harnessing AI and multi-omics in TwinsUK to unlock genetic and environmental drivers of skin ageing
Supervisors:
Dr Mario Falchi, Dr Helen Alexander
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Neuroscience and Mental Health
2025_80: Closed-loop experimentation platform to enable autonomous discovery lab
Supervisors:
Dr Miao Guo, Professor Adil Mardinoglu
Project themes:
1.Omics and Bioinformatics
2.AI, Machine Learning, and Multimodal Data
2025_81: Utilising responsible artificial intelligence for speech-based assessments of psychological and neurological disorders
Supervisors:
Dr Nicholas Cummins, Dr Ewan Carr
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Neuroscience and Mental Health
2025_82: Multimodal Prediction of Psychiatric Outcomes Using Structural Imaging, Blood Biomarkers, and Clinical Data from the KCL CRIS Dataset
Supervisors:
Dr Paris Alexandros Lalousis, Professor Nikolaos Koutsouleris
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
AI Modeling for Cardiovascular Risk Assessment in Menopausal Women
Supervisors:
Dr Petroula Laiou
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
2025_84: Computational simulation of stem cell function for enhancing muscle function in ageing and disease
Supervisors:
Dr Robert Knight, Dr Steffen Zschaler
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Neuroscience and Mental Health
2025_85: Use of machine learning and multi-omics to predict outcomes and direct ‘just in time’ care for patients with inflammatory eye disease
Supervisors:
Dr Tasanee Braithwaite, Dr Lei Lu
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_86: Use of machine learning to classify importance of genomic and clinical predictors for vision and health outcome following sight-threatening inflammation
Supervisors:
Dr Tasanee Braithwaite, Dr Pirro Hysi
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_87: Multimodal patient data streams to develop an AI-based Pipeline for Multi-Toxicity Predictive Models in Head and Neck Cancer Patients Treated with Radiotherapy
Supervisors:
Dr Teresa Guerrero Urbano, Professor Andy King
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Mobile Health and other patient generated/non-healthcare data
2025_88: Multi-institutional large-scale deep learning-based modelling of mandibular osteoradionecrosis using clinical data and dose distribution volumes: Phase II of the PREDMORN study
Supervisors:
Dr Teresa Guerrero Urbano, Professor Andy King
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_89: Predictive Modelling of Thromboembolic Diseases Using Physics-Informed Neural Networks
Supervisors:
Dr Adelaide De Vecchi, Professor Oleg Aslanidi
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Neuroscience and Mental Health
3.Mobile Health and other patient generated/non-healthcare data
2025_90: Collecting and Analysing Speech from Clinical Interviews from Community Mental Health Teams and linking with Electronic Health Records
Supervisors:
Dr Nicholas Cummins, Professor Richard Dobson
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
2025_91: AI/ML Approaches for Integrative Bioinformatics of Thoracic Cancer
Supervisors:
Dr Sophia Tsoka
Project themes:
1.Omics and Bioinformatics
2.AI, Machine Learning, and Multimodal Data
3.Imaging
2025_92: Improving management of oesophageal and lung cancer through multiomic data science
Supervisors:
Professor Vicky Goh, Dr Sophia Tsoka
Project themes:
1.Omics and Bioinformatics
2.EHRs, NLP, and LLMs
3.AI, Machine Learning, and Multimodal Data
4.Imaging
2025_93: Developing a Tool for Assessing Neuropsychiatric symptoms and its correlation with cognitive function in diverse ethnic communities
Supervisors:
Dr Zunera Khan, Dr Miguel Vasconcelos Da Silva
Project themes:
1.Omics and Bioinformatics
2.EHRs, NLP, and LLMs
3.AI, Machine Learning, and Multimodal Data
2025_94: Enhancing Patient Privacy: Differential Privacy in Federated Learning for Healthcare
Supervisors:
Dr Frederik Mallmann-Trenn
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
2025_95: Optimising Employment Outcomes in Early Psychosis: A Feasability Study of AI-Augmented Individual Placement & Support
Supervisors:
Dr Ricardo Twumasi, Dr Paris Alexandros Lalousis
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_96: Using AI to create living clinical guidelines for stroke
Supervisors:
Dr Iain Marshall, Professor Martin James
Project themes:
1.AI, Machine Learning, and Multimodal Data
2025_97: Understanding the impact of ICD-11 on stroke in the UK: Utilising live data to improve healthcare
Supervisors:
Dr Iain Marshall
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Neuroscience and Mental Health
2025_98: Using Artificial Intelligence to Predict Long-term Stroke Outcome from Combined Imaging and Clinical Data
Supervisors:
Dr Matthew O'Connell, Dr Iain Marshall
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_99: Integrative analyses of colon tissue epigenomic and multi-omic profiles with health record data towards a better understanding of the role of host-microbiome interactions on human health
Supervisors:
Professor Jordana Bell, Dr Kerrin Small
Project themes:
1.AI, Machine Learning, and Multimodal Data
2.Imaging
2025_100: Developing Mobile Health Foundation Models
Supervisors:
Dr Amos Folarin, Professor Richard Dobson
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_101: Machine learning in electronic health records for prognosis and diagnosis of rare neurological disorders
Supervisors:
Professor Richard Dobson
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_102: Temporal detection and analyses of interactions when combining multiple clinical guidelines, patient preferences and goals
Supervisors:
Professor Vasa Curcin
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
3.Neuroscience and Mental Health
2025_103: Modelling patterns of relapse in Multiple Myeloma
Supervisors:
Dr Arief Gunawan, Professor Richard Dobson,
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_104: Multimodal Epilepsy Lesion Detection with AI and Diffusion Imaging
Supervisors:
Dr Konrad Wagstyl, Dr J-Donald Tournier
Project themes:
1.Imaging
2.AI, Machine Learning, and Multimodal Data
2025_105: Design of a modular probabilistic expert system based on Object-Oriented Bayesian Networks to facilitate the interpretation and collation of toxicological findings
Supervisors:
Dr Matteo Gallidabino, Dr Vincenzo Abbate
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_106: Fair Multimodal AI for Cardiovascular Disease Characterisation
Supervisors:
Professor Andrew King, Dr Martin Bishop
Project themes:
1.Imaging
2.AI, Machine Learning, and Multimodal Data
2025_107: Detecting Frailty in electronic records using AI based approaches for Natural Language Processing and Large Language Models (LLM) on real world clinical text from multiple countries
Supervisors:
Professor Richard Dobson, Associate Professor Richard Beare, Professor James Teo
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_108: Strategies for investigating and addressing health inequalities in sexual and gender minority groups
Supervisors:
Dr Amal Khanolkar, Professor Laia Becares, Dr Martin Chapman
Project themes:
1.EHRs, NLP, and LLMs
2.AI, Machine Learning, and Multimodal Data
2025_109: Multimodal dental AI with uncertainty quantification
Supervisors:
Dr Yunpeng Li
Project themes:
1.AI, Machine Learning, and Multimodal Data
Detecting heroin/opioid overdose through analysis of data from wearables: developing a new emergency alert capability
Supervisors:
Professor John Strang
Professor Richard Dobson
Project themes:
1.AI, Machine Learning, and Multimodal Data
