Funded PhD Opportunity Analysis and Visualisation of Geo-Referenced Health Big Data

Subject: Computer Science and Informatics

Summary

The World Health Organization defines a healthy community as ‘one that is safe with affordable housing and accessible transportation systems, work for all who want to work, a healthy and safe environment with a sustainable ecosystem, and offers access to health care services which focus on prevention and staying healthy.’ A key focus in the University’s proposed strategy encompassing Civic Contribution is in support of these healthy communities, including ‘mental health, ageing, health innovation and policy, sport for life, history and heritage.’ This proposal therefore fits into the healthy communities’ research theme.

Understanding health and wellbeing is important at a global level as well as at a regional level in Northern Ireland. The work undertaken in this PhD project will use open data together with social media data to explore, analyse, and visualise health and wellbeing across the geography of Northern Ireland. Northern Ireland is now a producer of significant sets of open data relating to wellbeing and health including, for example, prescription data at GP practice level, which can be harnessed with census data relating to, for example, electoral ward level measures of deprivation and health.

Approximately 1 in 5 messages from social media datasets (e.g. Twitter, Facebook, Instagram, etc.) include geo-locational data, which provide an opportunity to analyse and identify geospatial patterns. The work undertaken in this PhD project will firstly develop a data warehouse to collate and maintain open and social media data. The data will then be provisioned for analysis using novel machine learning algorithms, specifically designed to manage and exploit the interrelationships between open and social data. All data will be processed to ensure that individuals cannot be identified. It will also be marked up semantically and data will be exposed for external use via a simple Application Programming Interface (API). This will result in an open, experimental platform capable of discovering temporal, geospatial, and other patterns of health and wellbeing, as well as visualising such patterns using appropriate interactive visualisation tools. The platform will be used to explore research questions relating to the geography of health and wellbeing across Northern Ireland.

The challenge in this PhD studentship is two-fold. Firstly, the successful applicant will work with the computer science supervisory team to construct the necessary software platform. Secondly, the supervision team will work with the successful applicant to co-create and refine the research questions. The computing academics will provide expertise in current computer science topics including software development, data analytics, and visualisation, as well as emerging topics such as visual analytics.

Candidates would be expected to use one or more of the following software technologies: Social media Application Programming Interfaces (API) including Twitter, GIS tools such as GeoServer, R programming with R Studio, Python, Ushahidi, Tableau and D3.JS.

Essential Criteria

  • Upper Second Class Honours (2:1) Degree from a UK institution (or overseas award deemed equivalent via UK NARIC)
  • Experience using research methods or other approaches relevant to the subject domain

Funding

    DFE

    The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £ 14,777 per annum for three years. EU applicants will only be eligible for the fees component of the studentship (no maintenance award is provided).  For Non EU nationals the candidate must be "settled" in the UK.

Other information

The Doctoral College at Ulster University

Launch of the Doctoral College

Current PhD researchers and an alumnus shared their experiences, career development and the social impact of their work at the launch of the Doctoral College at Ulster University.

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Key Dates

Submission Deadline
Wednesday 31 October 2018
Interview Date
November 2018

Contact Supervisor

Professor Maurice Mulvenna

Other Supervisors

Apply online

Visit https://www.ulster.ac.uk/applyonline and quote reference number #289270 when applying for this PhD opportunity