PhD Studentships: Developing Statistical Models for Estimating HIV Prevalence

My colleague Rosalba Radice is advertising a PhD studentship at Birbeck to work on developing statistical models for estimating HIV prevalence. Further details are available below and here: http://www.jobs.ac.uk/job/ALN048/bei-anniversary-phd-studentships-developing-statistical-models-for-estimating-hiv-prevalence.

Examples of the type of analysis involved include:

Marra, G., Radice, R., Till, B., Wood, S., McGovern, M., 2015. A Unified Modeling Approach to Estimating HIV Prevalence in Sub-Saharan African Countries. Research Report 324, Department of Statistical Science, University College London. http://www.ucl.ac.uk/statistics/research/pdfs/rr324.pdf

 

McGovern, M., Bärnighausen, T., Marra, G., Radice, R., 2015. On the Assumption of Bivariate Normality in Selection Models: A Copula Approach Applied to Estimating HIV Prevalence. Epidemiology 26, 229–327. http://www.ncbi.nlm.nih.gov/pubmed/25643102

BEI Anniversary PhD Studentships: Developing Statistical Models for Estimating HIV Prevalence

Birkbeck College, University of London - Department of Economics, Mathematics and Statistics

Qualification type: PhD

Location: London

Funding for: UK Students, EU Students

Funding amount: £16,057

Hours: Full Time

Placed on: 6th July 2015

Closes:  7th August 2015

Applications are invited for a BEI Anniversary studentship in the Department of Economics, Mathematics and Statistics, starting in October 2015. The studentship will cover fees at (Home/EU rate), plus an annual stipend of approximately £16,057. Closing date for applications is 7 August 2015.

The BEI Anniversary studentship is for applicants who are interested in the research area of Developing Statistical Models for Estimating HIV Prevalence. Candidates for the BEI Anniversary Studentship are expected to have a Master’s qualifications at  distinction level or, where this has yet to have been achieved, be able to provide evidence of high performance that will lead to a distinction. Applications are welcome from a range of cross-disciplinary backgrounds including statistics, biostatistics, computer science, epidemiology, public health.