Apologies for cross- and re-posting

//TWO WEEKS LEFT TO APPLY//

An exciting opportunity for a full-time, fully funded PhD scholarship is available in the Faculty of Health Sciences and Sport, University of Stirling.

Background information
Breast cancer is a global disease that impacts many people’s lives. While we know that mammography screening makes a difference to overall survival, it is at present not fully understood why levels of adherence to official screening programmes are falling in Scotland and other parts of Europe. Interrogation of secondary, quantitative data can assist in exploring the multifaceted drivers of this phenomenon and in finding plausible explanations that can be translated into effective initiatives directed towards improving health. This project aims to develop a statistical model that can assist in the prediction of risks associated with adherence patterns among women attending mammography screening. With an officially reported attendance of ~70% of invited women (and decreasing in the past years), this remains significantly lower than the UK-wide target of 80%.

This project will go through the following steps:

i. Reviewing the relevant literature.
ii. Synthesising it.
iii. Developing novel and improved indicators to identify the main drivers of adherence to breast screening for Scottish women.
iv. The final step will be to build and validate a predictive model aimed at providing reliable additional insight to inform public health policies to consistently increase attendance and reduce mortality.

The project will utilise data from the Information and Statistics Division, Scotland and other health data sets as relevant. Therefore, this PhD project would suit an individual who wishes to pursue a quantitative set of methodologies in the field of health research, especially in relation to the analysis of complex linked data sources.

The supervisors of the project are:

Dr Federico Andreis, Lecturer Statistician, University of Stirling
Dr Susanne Cruickshank, Associate Professor in Cancer Nursing, University of Stirling
Dr Tony Robertson, Lecturer in Social Epidemiology and Public Health, University of Stirling

Candidates are welcome to make informal enquiries about the project to Dr Federico Andreis ([log in to unmask])

Eligibility and availability
The successful candidate should have: 

- A 1st or 2:1 degree in Statistics or a Health/Social Science subject with a strong statistical component
- A Master degree in a relevant topic area (e.g. statistics/quantitative methods, health sciences, public health)
- An interest in spatial and temporal modelling of complex health data
- An interest in the research areas and methodologies involved in the project
- Good command of at least one package for statistical computing (for example R, Stata and others)

Applications will be assessed by the project team and shortlisted applicants may be invited to an interview late July/early August. The successful candidate will be based in the Faculty of Health Sciences and Sport in the Pathfoot Building, University of Stirling. It is anticipated the candidate will start in September 2019 (flexible).

How do I apply?
Applicants are asked to send in all the documentation listed below, attached as a single email, to [log in to unmask] using the subject header ‘Breast Screening Adherence Application’.

Deadline is 23:59 on 30 June 2019.

Documents to attach include:
Academic Transcript and Degree Certificate(s)
Final degree transcripts including grades and degree certificates (and official translations, if needed) - scanned copy in colour of the original documents.

References
Two references on headed paper (academic and/or professional). At least one reference must be academic. The other can be academic or professional. Your references should be on official headed paper. These should also be signed by the referee. If your referees would prefer to provide confidential references direct to the University then we can also accept the reference by email, from the referee’s official university or business email account to [log in to unmask] clearly labelling the reference e.g. ‘Breast Screening Adherence Reference’

Copy of CV
Detailing relevant education and work experience.

Applicant Statement
A brief 1-page letter of motivation, outlining your research interests and your thoughts on how you could contribute to our research agenda.

You may leave the list at any time by sending the command

SIGNOFF allstat

to [log in to unmask], leaving the subject line blank.