 |
 |
PhD CASE Studentship: Developing synthetic data methods for large confidential administrative databases Lancaster University, Department of Mathematics & Statistics Funding is available for either a 1+3 (MSc+PhD) or +3 (PhD) studentship between the Department of Mathematics & Statistics at Lancaster University and our industry partner the Official for National Statistics (ONS), funded by the ESRC – Northwest Social Science Doctoral Training Partnership. The studentship includes payment of tuition fees and an annual maintenance grant of £14,777 (tax-free) together with an advanced quantitative methods enhancement of an extra £3000 for the three years of the PhD. The start date is 1st October 2019. Dr. Robin Mitra and Prof. Brian Francis from the Department of Mathematics & Statistics, Lancaster University and Iain Dove from the ONS will supervise the project. Non UK/EU citizens are eligible to apply. Description of the project: There is a demand from social scientists to access high quality data for research, traditionally large social surveys. These are costly which has prompted a shift to making routinely collected administrative data more available to researchers. The government open data access policy has also led to an initiative to make the administrative data their departments hold, available more widely. These databases typically contain information on a large number of records with potentially sensitive information, and have severely restricted access. This has led to investigating ways to improve access to government administrative databases without compromising confidentiality. Synthetic data is an increasingly popular approach to address this problem. The approach replaces the data with synthetic values drawn from a statistical model fit to the original data. This is typically done multiple times to generate multiple synthetic data sets. As the data now comprise only synthetic values, confidentiality should have been protected, and providing a plausible model has been used, statistical properties should be preserved. Synthetic data would give researchers the ability to test their methodology on a synthetic version prior to analysis of the original data. This project will develop synthetic data methods for confidential administrative databases, ultimately leading to improved access to valueable administrative data sources. The PhD project will involve developing novel modelling techniques to handle challenges in synthesizing large administrative databases, as well as developing appropriate risk and utility metrics. It is also anticipated that an R package will be developed that implement the methods developed in this project. The PhD project will involve working alongside staff at the ONS, and require visits to the ONS office in Titchfield, Hampshire, at regular intervals. Academic Requirements: A first-class degree (or equivalent) for MSc+PhD and a good Master’s degree (or equivalent) for the PhD in an appropriate subject. How to apply: Details for applying can be found at: https://www.lancaster.ac.uk/maths/study/phd/ Please include a cover letter that should clearly explain your motivation for applying for this specific studentship. Applications will be considered as they are received. Please contact Dr. Robin Mitra ([log in to unmask]) for more information about the studentship. Deadline for applications: 25th February 2019 (23.59 UK time) You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.