Position Summary
Applications are invited for a cutting-edge 3-year Ph.D. project in healthcare analytics hosted in the Department of Computer Science, University of Surrey, UK.
Electronic health records contain a wealth of information that has not yet been fully exploited. Today, it is possible to retrieve millions of patient records over time, across vendors, and care professionals from primary, secondary to tertiary care.
This research project aims to develop a set of statistical tools for processing population-scale linked health records, that is, in the order of millions of patient records which are joined up from different care establishments and possibly other external data sources. Although a number of statistical software packages exist, there is still room for very substantial improvement, e.g., by designing better algorithms for handling sampling bias, structural noise, irregularity and under sampling of data; for handling covariates or confounding factors; exploiting temporal logics; and, not least, for efficient retrieval of similar patient profiles.
The work will concentrate upon novel pattern recognition, machine learning, and data-mining techniques. Knowledge and experience in multi-task learning, hierarchical modelling, statistical adaptation, kernel or other non-parametric methods, and/or deep-learning are desirable.
Department of Computer Science
The Department of Computer Science at the University of Surrey, within the Faculty of Engineering and Physical Sciences, has an international reputation for research and teaching. In the National Student Survey of 2015/16, overall student satisfaction was 95%. Research in the department is focussed on two main areas: Nature Inspired Computing and Engineering, and Secure Systems, with Surrey recognised by GCHQ as one of only thirteen Academic Centres of Excellence in Cyber Security Research. Its security related research is focused on protocol analysis, security verification, trusted computing, data privacy, access control, privacy-preserving architectures, vulnerability analysis, distributed ledger technologies, digital forensics and human-centred computing.
Responsibilities
The candidate will contribute towards building a critical mass of competency in healthcare analyticswithin the Department of Computer Science. He/she will be embedded in the MRC CKD research team currently consisting of two full-time postdoctoral MRC Research Fellows working in a multidisciplinary team involving clinicians and IT engineers. The team is part of the larger Nature Inspired Computing Engineering group with expertise in machine learning and optimization.
Qualifications
To apply you should have at least an upper second class honours degree in Computer Science, or a suitable hard science or other engineering subject. Preference will be given to those with appropriate M.Sc. or equivalent research/industrial experience in data analysis and/or machine learning. It is not mandatory to have the experience of working with clinical/health/biology data but this can be advantageous.
The candidate is expected to be able to use or modify existing statistical tools or methodologies in order to solve novel problems posed by healthcare analytics. Familiarity with Matlab, Python, R, or SPSS is desirable.
In addition, you must have good communication skills and be fluent in English. We look for a candidate that is self-motivated, engaging, and is a team player.
Studentship Funding
The Studentship consists of a fee waiver and a stipend of £16,000 per annum for three years and is available to students of UK/EU residency.
Non-EU students are also welcome to apply but they would be expected to cover the fee difference annually.
The position is intended to start in April 2017 or as soon as possible thereafter.
As a PhD student at University of Surrey, you have many opportunities to participate at conferences, projects and other relevant events which will extend your professional network and benefit your future career. Successful candidates will be expected to provide support in the Department’s course portfolio by helping out in lab sessions.
Application Procedure
The application process requires the submission of a CV, two letters of recommendation or contact information of two referees, attested copies of degree certificates and transcripts from all university-level courses taken. More information about how to apply can be found in the Computer Science PhD page by clicking on the ‘apply online’ button.
In addition to the above, as part of your application, you are also required to upload the following documents:
- Statement of purpose (1-3 pages) where you introduce yourself, explain why you want to pursue a PhD, present your qualifications and describe your future research plans;
- Research proposal describing your research area of interest and motivation. Are there any specific projects and research issues you are primarily interested in? Previous research fields and main research results should also be mentioned. It is important to include parts of your own work such as theses and articles that you have authored or co-authored.
Shortlisted applicants will be contacted directly to arrange a suitable time for an interview.
For any questions regarding the application process or an informal discussion about the position, please contact Dr. Norman Poh on n.poh@surrey.ac.uk +44 1483 68 6136.
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For more information click "Further official information" below.
This opportunity has expired. It was originally published here:
http://www.surrey.ac.uk/projects/phd-studentship-population-scale-healthcare-analytics