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Multi-source knowledge base and medical data analytics for clinical and operational intelligence

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  • Full or part time
    Dr Weizi Vicky Li
    Prof Keiichi Nakata
    Mr Eghosa Bazuaye
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

Applicants are invited to undertake a full PhD studentship in partnership with industry to address key challenges in knowledge management and data analytics from electronic patient record and various information systems in the hospital. The candidate will be supervised by both Informatics Research Centre at University of Reading and the Informatics department of Royal Berkshire Hospital. This PhD project will firstly focus on multi-source data warehouse and knowledge base (general and pathway specific) development from various information systems and electronic patient record; secondly to conduct data analytics and report development to support clinical decision support and improve operational efficiency and data assurance.

This PhD project is based on existing hospital information systems and a centralized SQL based data warehouse with data sourced from over 16 clinical systems from across the Royal Berkshire Hospital. The Hospital also utilizes a range of technologies to support data capture, analytics and reporting, these include Microsoft BI stack, Tableau and asp,net. This project will further establish the knowledge base from multiple data sources in order to support the analytics and report development from multiple dimensions.

This is an exciting PhD project that has a combination of academic and industrial challenges which will enhance the student’s ability to tackle complex intellectual and practical aspects of healthcare data and contribute to the application in real predictive clinical decision support. The candidate will be supervised by Dr Weizi Vicky Li and Eghosa Bazuaye the Associate Director of Informatics at the Royal Berkshire Hospital.

We are seeking talented candidates with:
• Master degree with distinction, in areas of information management/data science/health informatics/computer science
• Must be experienced/confident in data mining, analytics and report development.
• Experience in database management, data warehouse, information and knowledge fusion and relevant software environment will be an advantage
• Experience and medical knowledge/background will be an advantage
• Fluent English speaking & strong academic writing skills (e.g. IELTS 7 or TOEFL 100 above )
• Ability and track record in academic journal publication are desirable
• Candidates should have an autonomous and proactive working style, good communication skills and the ability to work in a team

This is an excellent opportunity to work on a novel medical knowledge base and data analytics methods with strong links to medical and healthcare applications and key skills and knowledge in preparation for a high-impact, high-technology research or industrial career.

In addition we would also like you to send a sample of your written work. This might be a published conference or journal paper, or a chapter of your final year dissertation.

How to apply: To apply for this studentship please submit an application for a PhD in Informatics and System Science http://www.reading.ac.uk/graduateschool/prospectivestudents/gs-how-to-apply.aspx

*Important note* Please quote the reference ‘RBH-UOR’ in the ‘Scholarships applied for’ box which appears within the Funding Section of your on-line application.

Informal enquiries can be made by email to Dr Weizi Vicky Li ([email protected]) and Bazuaye Eghosa ([email protected])

Please note that, where a candidate is successful in being awarded funding, this will be confirmed via a formal studentship award letter; this will be provided separately from any Offer of Admission and will be subject to standard checks for eligibility and other criteria.

Funding Notes

-Full tuition fee + stipend funded for three years
-Starts September 2017
-3-year award
Tuition fee plus stipend, full-time PhD based in Reading, UK.

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