About the Project
This studentship is funded by the College of Life Sciences and is placed within the supportive and nurturing environment provided by the Department of Respiratory Sciences, the Leicester Biomedical Research Centre and the Leicester Precision Medicine Institute.
You will receive financial backing and the support of an inclusive and collaborative research culture - enabling you to realise your potential. Additional opportunities to link the program to other relevant University networks including the Leicester Artificial Intelligence Network (LAIN) and Departments (e.g. Computer Science) will be explored during the PhD according to the context of the project and the interests of the student.
The PhD project will involve statistical analysis of time series data in clinical trials, with a view to optimising precision medicine endpoints in severe asthma. A systematic review of the literature on asthma attack statistical models will also be conducted.
The PhD program will support a nationally funded NIHR-EME clinical platform trial (BEAT-Severe Asthma: coordinated by Prof Siddiqui and Hosted by the Leicester Clinical Trials Unit). The trial will be collecting and curating daily monitoring data in patients with severe asthma randomised to trial therapies or placebo with a view to both developing new and applying existing [1,2] statistical models of asthma attacks and treatment response.
Opportunities will be available to develop statistical models using legacy clinical trial data.
Entry requirements
• UK Bachelor Degree with at least a 2:1 in statistics or data science
• Expertise in statistical programming in standard environments such as R and Python is an essential requirement
University of Leicester English language requirements apply (where applicable).
How to apply
Please refer to https://le.ac.uk/study/research-degrees/funded-opportunities/cls-respiratory-siddique-1
Within the application form, please:
• Specify that you wish to apply for an College of Life Sciences, Department of Respiratory Sciences, 2020 Studentship
• Include the project title
• Include the names of the project supervisors
References
1.Fuhlbrigge AL et al. A novel endpoint for exacerbations in asthma to accelerate clinical development: a post-hoc analysis of randomised controlled trials. Lancet Respir Med. 2017 Jul;5(7):577-590.
2. Delgado-Eckert E et al. Functional phenotypes determined by fluctuation-based clustering of lung function measurements in healthy and asthmatic cohort participants. Thorax. 2018 Feb;73(2):107-115.
