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Medical Statistics PhD Projects, Programmes & Scholarships in the UK
We have 30 Medical Statistics PhD Projects, Programmes & Scholarships in the UK
We have 30 Medical Statistics PhD Projects, Programmes & Scholarships in the UK
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Machine Learning for Structural Damage Detection in Psoriatic Arthritis Hand Radiographs
The University of Bath is inviting applications for the following fully funded PhD project commencing in October 2023. Supervisory Team. Read more
Are macrophages the heroes or villains of infection control?
The field of host pathogen interactions has never been more important. From the recent Covid19 pandemic to the causes of cancer and neurodegenerative disease host pathogen interactions underpin the pathology of many important diseases. Read more
Global Doctoral scholarship – St Andrews and Bonn – Medicine
The University of St Andrews and the University of Bonn are pleased to offer a scholarship funded by both institutions, to support an exceptional student undertaking doctoral research in the following area. Read more
Integrating protein data into large international resources to address clinical challenges in prostate cancer
Research Group:
Statistical Medicine and Molecular Biology
The University of St Andrews and Macquarie University are pleased to offer a scholarship funded by both institutions, to support an exceptional student undertaking doctoral research in the following project. Read more
Using viral sequence data to understand COVID-19 spread in health care settings
This project is one of 15 four year PhD Studentships funded by Medical Research Scotland (MRS) (. https://www.medicalresearchscotland.org.uk. Read more
Advancing the field of flooring for fall-related injury prevention in older people: developing a core outcome set and informing intervention design
Applications are invited for a fully-funded three year PhD to commence in October 2023. The PhD will be based in the Faculty of Science and Health, and will be supervised by. Read more
Predicting response to breast cancer therapies using integrative multiplatform profiling
Breast cancer continues to have a high mortality rate, which can in part be explained by the fact that patients are treated with ‘one size fits many’ therapies that are agnostic to the molecular complexity of the tumour ecosystem (Rueda and Sammut et al., Nature 2019). Read more
Last chance to apply
Comprehensive multi-omic analyses of “islands of resistance” tumour cells to identify aromatase inhibitor resistant subclones in oestrogen receptor positive breast cancer
Over 80% of breast cancer (BC) patients in the developed western world have oestrogen receptor (ER)–positive disease; their treatment normally includes surgery and adjuvant endocrine therapy, and sometimes chemotherapy which greatly improves survival outcome (1). Read more
Young people, urban green and blue space use, and barriers.
This studentship will investigate the current mental health crisis and explore how this is influencing urban green and blue spaces (UGBS) use in young people, as well as how urban green and blue spaces may help to mitigate poor mental health in this group. . Read more
Longitudinal trends in asthma mortality and uncontrolled asthma, and predictors for asthma-related deaths in children living in England
The 2014 National Review of Asthma Deaths (NRAD) (1) reported the detailed findings from a review of 195 asthma deaths (28 children and young people ≤ 19 years old) occurring in the UK between February 2012 and January 2013. Read more
A Multi-Omics approach to understanding cardiovascular risk in patients with End-Stage Kidney Disease
Background. End-stage Kidney failure, also known as End-Stage Kidney Disease (ESKD), is the final, irreversible stage of chronic kidney disease (CKD), where kidney function has worsened to the point that the kidneys can no longer function independently. Read more
Transforming neuro-pathology with deep learning (ref: SF22/HLS/APP/Schwalbe)
Medulloblastoma is the most common central nervous system tumour of childhood. Although advances in treatment have raised survival to ~75%, there remains significant numbers of patients who die of their disease. Read more
Modelling non-standard longitudinal outcomes using fast Bayesian inference.
Repeated observations over time on individual patients allows the opportunity to analyse factors that influence the changes over time in a variable of interest. Read more
Kernel methods for system identification with application to the analysis and classification of cardiovascular time series
Supervisory Team: Dr Andrea Lecchini-Visintini, Prof David Simpson. Project description. Read more
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