Queen’s Belfast Funded PhD in Predictive Analytics for Innovation Policy
Queen’s Business School, Belfast
Three-year fully funded Queen’s Belfast PhD on predictive analytics for innovation policy, supervised by Professor V. Charles. Home tuition plus tax-free stipends from £21,819 to £24,055 by year; deadline 13 November 2026.
Queen’s Business School is recruiting a PhD researcher to develop and validate machine-learning models that can help Invest NI target innovation-policy support. The project is delivered with Ulster University, Invest NI and the Artificial Intelligence Collaboration Centre. It examines model robustness, explainability and responsible use of analytics in public decision-making. The preferred start is 11 January 2027. Applications close Friday 13 November 2026 at 3 p.m. UK time. Apply through Queen’s postgraduate research portal and identify the funded project by its full title.
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Recorded source check: October 22, 2026. A stored check date does not guarantee that every field is complete or still current. Compare the provider, eligibility, funding and deadline with the live official call before applying.
Benefits
Home tuition fees and tax-free maintenance allowance of £21,819 in 2026/27, £22,910 in 2027/28 and £24,055 in 2028/29, subject to satisfactory progress. Additional research, training and conference support may be available subject to approval and policy.
Eligibility summary
Restricted to eligible UK and Republic of Ireland candidates because of secure data access. Applicants must be a UK national, Irish national, or hold settled/pre-settled status or indefinite leave, and meet the specified three-year residency requirement in the EEA, Switzerland, UK or Gibraltar. A relevant 2:1 honours degree or accepted equivalent and quantitative/analytical ability are required. Existing PhD holders and those already registered on a research doctorate for more than one full-time year are ineligible.
Requirements
Interest in applied, policy-focused predictive analytics; quantitative methods, statistical or machine-learning skills; capacity to use Python or R; ability to work with structured data and explain findings to policy stakeholders.
Documents required
CV and a 1,000-word cover letter covering motivation, relevant quantitative/programming or research experience, applied policy interests, and how essential criteria are met. Submit through Queen’s postgraduate research portal.
Language/test requirements
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