The University of Bristol, Faculty of Engineering, is offering a fully funded four-year PhD studentship in Learning and Decision-Making Under Uncertainty in Public Health, beginning in the 2027/28 academic year. The project focuses on developing machine learning and statistical methods for adaptive learning, reinforcement learning, and sequential decision-making, with applications in public health and epidemiology. Funding is open to UK, EU, and international applicants worldwide, with selection on a competitive basis.
Important Dates / Deadline
- Application Deadline: January 31, 2027
- Scholarship Start: 2027/28 academic year
- Funding Duration: 4 years
- Study Mode: Full-time
- Appointment Type: Contract/temporary
Organization
University of Bristol, Faculty of Engineering.
Research Supervisor: Dr. Mengyan Zhang
Supervisor Website: https://mengyanz.github.io/
Location / Study Destination
Bristol, United Kingdom.
Who Can Apply
Country Eligibility: Open Worldwide, No Nationality Restriction Specified.
The studentship explicitly welcomes applicants from the United Kingdom, European Union, and other countries worldwide. International applicants are eligible to compete for the advertised funding.
The ideal candidate should demonstrate:
- Foundational knowledge of machine learning.
- Strong self-motivation and an interest in independent research.
- Interest in artificial intelligence, statistical learning, and sequential decision-making.
- Motivation to develop computational methods for public health and epidemiological applications.
- Willingness to undertake interdisciplinary research combining AI, statistics, and public health.
Key Benefits / Funding
The studentship provides a competitive four-year University Scholarship.
- Tuition Fees: Fully covered.
- Annual Stipend: Minimum tax-free stipend at the applicable UKRI rate.
- Stipend Reference: £20,780 per year at the 2025/26 UKRI standard rate.
- Research Training Support Grant (RTSG): £8,400.
- Funding Duration: 4 years.
- Funding Eligibility: UK, EU, and international applicants.
- Academic Start: 2027/28.
The £20,780 stipend figure is the published 2025/26 reference rate. The actual stipend for the 2027/28 academic year will follow the applicable UKRI rate.
The studentship also provides opportunities for research in advanced machine learning, probabilistic modeling, reinforcement learning, and public health applications.
Main Requirements
Applicants should have foundational knowledge of machine learning and demonstrate strong motivation for doctoral research.
The PhD project will focus on three primary research directions:
- Adaptive Data Acquisition: Develop strategies that maximize information gain while accounting for limited resources.
- Reinforcement Learning for Intervention and Control: Investigate reinforcement learning methods for sequential decision-making and intervention planning.
- Robust Learning Under Uncertainty: Design learning methods that adapt to incomplete observations, evolving environments, and distributional shifts.
The research will integrate several methodological areas, including:
- Reinforcement learning and active learning.
- Bayesian decision theory.
- Stochastic optimization.
- Probabilistic modeling.
- Network-based representations.
- Scalable and interpretable artificial intelligence.
Potential public health applications include adaptive disease surveillance, outbreak monitoring, resource allocation, and intervention planning using dynamic mobility and contact networks.
How to Apply
Applicants should complete the university’s online application process and email the required application materials to the research supervisor.
Online Application Portal: University of Bristol Postgraduate Application
Supervisor: Dr. Mengyan Zhang
Application Email: mengyan.zhang@bristol.ac.uk
Required Email Subject: PhD Application + Your name
Application steps:
- Access the University of Bristol postgraduate application portal.
- Select the appropriate PhD program on the Programme Choice page.
- Enter the studentship information in the Funding and Research Details sections.
- Prepare the required application documents.
- Email the application materials to mengyan.zhang@bristol.ac.uk using the specified subject line.
- Complete the application before January 31, 2027.
Documents Needed
Applicants should prepare the following materials:
- Curriculum Vitae (CV): Summarize academic qualifications, relevant experience, technical skills, and research achievements.
- Personal Statement: A one- to two-page document introducing the applicant and explaining their motivation for pursuing PhD research.
- Academic Transcripts: Transcripts for all qualifying degrees, including completed degrees and degrees currently underway.
- Research Proposal: Optional but preferred. Applicants are encouraged to include a proposal relevant to the research project.
- Additional Supporting Materials: Relevant research publications, research outputs, thesis work, coding repositories, or other materials demonstrating research potential.
Important Notes
- Country Eligibility: Open to applicants worldwide, including UK, EU, and international students. No country-specific nationality restriction is indicated.
- Competitive Funding: The studentship offers competitive worldwide funding, and eligibility does not guarantee an award.
- Full Tuition Coverage: The advertised scholarship covers tuition fees for eligible successful applicants.
- Stipend Reference: The advertised £20,780 annual stipend is based on the 2025/26 UKRI rate, rather than a confirmed 2027/28 amount.
- Research Training Support: The funding package includes an RTSG amount of £8,400.
- Research Proposal: Submission is optional but preferred.
- Shortlisting: Due to the volume of inquiries, only shortlisted candidates may receive a response.
- Research Supervision: The project will be supervised by Dr. Mengyan Zhang, whose research focuses on sequential decision-making and public health.
- Research Network: The supervisor collaborates with researchers through the Machine Learning and Global Health network, including researchers at the University of Oxford, Imperial College London, and the National University of Singapore.
- Application Program Selection: Applicants should confirm the appropriate program title when completing the online application, as the supplied instructions do not identify a specific program title.
