Senior Research Associate

Lancaster University
February 12, 2024
Offerd Salary:£38,205
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Contract Type:Other
Working Time:Negotigation
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Senior Research Associate

Mathematics & Statistics Salary: £38,205 Closing Date: Monday 12 February 2024 Interview Date: Tuesday 27 February 2024 Reference: 1420-23

We are seeking applications for a Senior Research Associate to work within the Department of Mathematics and Statistics at Lancaster University, as a part of the Horizon Europe funded project, "Preventable: Sustainable care for rare tumour risk syndromes."

Rare tumour risk syndromes (RTRS) are a set of rare diseases (affecting approximately 5 per 10 000 people or less using the European definition), which are genetically determined from birth. Lifetime risk of cancer in individuals suffering from RTRS can be as high as 100%. The Preventable project aims to assess the clinical, social, and financial impact of applying multidisciplinary and specialized care to prevent advanced disease in families suffering from RTRS.

The project will use multicentric clinical data to model the disease onset or progression and the differences in outcomes and costs of primary/secondary prevention measures and/or treatment in RTRS carriers, taking forward work already developed. Patient populations for individual risk syndromes are generally small (since we are referring to rare syndromes) and hence data is intrinsically limited. In addition, the direct evidence is observational, partially retrospective, and prone to confounding, particularly with respect to the patients who do not opt for preventative surgery.

Your role will be to develop novel statistical modelling approaches to overcome the challenges in the data. The work will adapt and extend Bayesian model averaging methods proposed for the analysis of basket trials to construct an appropriate relative survival model where information can be borrowed between risk syndromes in a data-driven way.

You will also assist in the development and implementation of decision analytic cost-effectiveness models. Different risk syndromes have distinct cancer risk-profiles and different preventative treatments, hence they may have quite different associated cost-effectiveness. Separate decision analytic models will be constructed for each tumour risk syndrome within an overarching framework, using the estimates from statistical modelling as inputs.

You should have completed, or be close to completing a PhD in Statistics, or a closely related discipline. You will have the demonstrated the ability to develop new statistical methodology. A demonstrable ability to produce academic writing of the highest publishable quality is essential. Previous knowledge or experience of Bayesian modelling, survival and event history analysis or cost-effectiveness modelling would be advantageous, but is not essential.

The position is available from April 1st 2023 or as soon thereafter as is convenient, and will run for 16 months. Interviews will be carried out shortly after the closing date.

We welcome applications from people in all diversity groups.

Interested candidates are encouraged to informally contact Prof Andrew Titman ([email protected]) if they have any queries about the position.

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