Adaptive treatment and robust control
Prof R Henderson
Prof NJ Young
No more applications being accepted
Competition Funded PhD Project (Students Worldwide)
This studentship is available as part of a three-way collaboration between researchers in statistics, in engineering, and in mathematical analysis. The aim is to solve an array of problems in the general area of adaptive intervention, through the integration of techniques and approaches that have been developed in distinct ways in the three fields, specifically optimal dynamic treatment methodology in statistics and control theory in engineering and analysis. The studentship is to be primarily focused on the statistical aspects of this programme and the general statistical areas include causal inference, longitudinal data analysis and missing data problems.
The specific task is to derive adaptive decision rules for medical treatments or other interventions based on subject-specific characteristics and individual biomarker trajectories. For example, the optimum dose of warfarin anticoagulation treatment varies over time as a function of lifestyle and other patient-specific factors. The aim is to build a decision rule which uses the patient’s prior history to provide clinicians with guidance as to the best dose to prescribe. Other applications include chemotherapy for leukaemia patients, controlling animal growth rate and training of racing horses.
This studentships is available to UK/EU and International candidates, who have/expect a 2:1 honours degree in computing science, mathematics, physics, statistics or another strongly quantitative discipline, or an international equivalent.
Applicants whose first language is not English require a minimum of IELTS 6.5. International applicants may require an ATAS (Academic Technology Approval Scheme) clearance certificate prior to obtaining their visa and to study on this programme.
The studentship includes tuition fees, a tax-free stipend of (up to) £13,863pa (14/15 level), a desktop computer, and £1500 travel allowance.
How good is research at Newcastle University in Mathematical Sciences?
FTE Category A staff submitted: 20.40
Research output data provided by the Research Excellence Framework (REF)
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