PHD Data-Driven Decisions: Transforming Urgent Care Patient Outcomes and Resource Allocation for the Northern Ireland Ambulance Service
PhD @Queen’s University Belfast posted 6 days agoJob Description
Overview
The Northern Ireland Ambulance Service (NIAS) is geographically the largest of six Health and Social Care Trusts in NI, serving a diverse region of 1.9 million people with 46 stations spread out over 5345 square-miles. NIAS services include both emergency and non- emergency response, including transport for those most vulnerable in society to hospital appointments.
NIAS is currently operating under the ‘highest level of pressure ever’ and the demand for the service exceeds the available capacity. The team need to achieve several objectives: (i) have a model that predicts patient outcomes and deterioration rates from 999 calls, and (ii) determine the optimal deployment strategy for a new ‘Advanced Paramedic’ (APUC) service.
The project will require skills in predictive modelling, machine learning, spatio-temporal modelling, and stochastic simulation.
A strong background in Mathematics and Statistics is required for this project. Experience with Python will be considered an advantage.
Funding Information
To be eligible for consideration for a Home DfE (covering tuition fees and maintenance stipend of approx. £19,237 per annum), a candidate must satisfy all the eligibility criteria based on nationality, residency and academic qualifications.
To be classed as a Home student, candidates must meet the following criteria and the associated residency requirements:
• Be a UK National,
or • Have settled status,
or • Have pre-settled status,
or • Have indefinite leave to remain or enter the UK.
Mathematics overview
The Mathematical Research Centre conducts world-class research in the following areas: Algebra, Analysis, Operator Algebras, Algebraic Topology, Topological Data Analysis, PDEs, Survival Analysis, Bayesian Networks, Data Analytics and Operational Research. It maintains vibrant international links with a large number of researchers around the globe and regularly hosts international conferences and research visitors.
Mathematics at Queen’s is ranked 20th in the UK (Complete University Guide 2025). 88% of research submitted by Queen’s has been assessed as world-leading or internationally excellent.
List of researchers, their interests and upcoming PhD projects can be found at:
https://www.qub.ac.uk/research-centres/msrc/research/interests/
Mode of study / duration
Registration is on a full-time or part-time basis, under the direction of a supervisory team appointed by the University. You will be expected to submit your thesis at the end of three years of full-time registration for PhD, or two years for MPhil (or part-time equivalent).
Mathematics Highlights
Industry Links
- The School has many industry links, some of which are with Seagate Technology R&D, Andor Technology and AVX Ltd. Many of our graduates take up positions with these companies in posts such as Statistical Analysis Programmer, Trainee Accountant, Financial Engineer and Business Analyst.
Career Development
- Queen’s is ranked 8th in the UK for Graduate Prospects – On Track (Complete University Guide 2025) Graduates from the School take up employment through a number of companies such as Allstate, AquaQ Analytics, Citigroup, Deloitte, PwC, Randox, Seagate and UCAS.
World Class Facilities
- Since 2014, the School has invested over £12 million in new world-class student and staff facilities. Maths and Physics students now have their own teaching centre that opened in 2016 housing experimental physics laboratories, two large computer rooms for mathematical simulations and student study plus a student interaction area.
In addition, Belfast has the lowest cost of living in the UK (Mercer Cost of Living City Ranking 2023).
Key Facts
- Students will have access to our facilities, resources and our dedicated staff. The School of Mathematics and Physics is one of the largest Schools in the University. Staff are involved in cutting-edge research that spans a multitude of fields.
