assembled one of the world's most comprehensive collections of clinical, imaging, laboratory, pathological and long-term outcome data for prostate cancer research.
This PhD studentship will develop and apply innovative statistical and machine learning approaches to improve prediction of prostate cancer outcomes using multimodal data from ReIMAGINE[Life]. The successful candidate will work within Work Package 3 (Advanced Statistical Modelling), jointly led by Professor Mieke Van Hemelrijck (King's College London) and Professor Ton Coolen (Radboud University Medical Center).
The project will focus on integrating diverse sources of information, including clinical characteristics, imaging-derived features, biomarkers and longitudinal follow-up data, to identify patient subgroups with distinct disease trajectories and outcome risks. The student will develop and evaluate advanced prediction models using state-of-the-art Bayesian statistical methods, survival analysis techniques and machine learning approaches. Particular emphasis will be placed on understanding disease heterogeneity, identifying novel risk signatures, and improving prediction of clinically significant outcomes such as disease progression, metastasis and prostate cancer-specific mortality.
The student will have access to unique datasets generated through the ReIMAGINE[Life] programme and will collaborate with an internationally recognised multidisciplinary team of epidemiologists, statisticians, clinicians, imaging scientists and data scientists. The project offers opportunities to contribute both methodological advances and clinically relevant discoveries that support the development of precision medicine approaches in prostate cancer.
The studentship will provide comprehensive training in cancer epidemiology, advanced statistical modelling, machine learning, risk prediction, and analysis of complex health data. The successful candidate will gain experience working with large-scale multimodal datasets and will be supported to present findings at national and international scientific conferences and publish in leading peer-reviewed journals.
Funding Notes
Funded by Prostate Cancer UK, this studentship will provide support for tuition fees and a tax-free stipend at the prevailing Prostate Cancer UK rate for the duration of the award. The student will join the multidisciplinary ReIMAGINE[Life] research programme and benefit from training in advanced statistical modelling, cancer epidemiology and health data science.
References
Marsden T, et al. The ReIMAGINE prostate cancer risk study protocol: A prospective cohort study in men with a suspicion of prostate cancer who are referred onto an MRI-based diagnostic pathway with donation of tissue, blood and urine for biomarker analyses. PLoS One. 2021
Santaolalla A, et al. The ReIMAGINE Multimodal Warehouse: Using Artificial Intelligence for Accurate Risk Stratification of Prostate Cancer. Front Artif Intell. 2021
Rowley M, et al. A latent class model for competing risks. Stat Med. 2017
