At a Glance
- Tasks: Conduct groundbreaking research in AI and public health decision-making under uncertainty.
- Company: Join a leading university with a focus on innovative research and collaboration.
- Benefits: Receive a competitive stipend, full tuition coverage, and funding for research activities.
- Other info: Work under renowned Dr. Mengyan Zhang with opportunities for global collaboration.
- Why this job: Make a real impact in public health while advancing your career in AI and data science.
- Qualifications: Strong foundation in machine learning and self-motivation required.
The predicted salary is between 63000 - 77000 £ per year.
Funding for: Competitive Worldwide Funding
Funding amount: 4 year University Scholarship starting 27/28 academic year. Minimum tax-free stipend at the current UKRI rate (for 2025/26 standard stipend is £20,780, RTSG £8,400, full Tuition Fee covered).
Hours: Full time
Contract: Contract/temporary
Closing date: 31/01/2027
The project: Decision-making under uncertainty is a fundamental challenge in AI and data science, particularly in dynamic settings where observations are collected sequentially and decisions influence future outcomes. This project will develop novel machine learning and statistical methods for adaptive learning, sequential decision-making, and control, motivated by applications in public health and epidemiology.
The project will focus on methodological advances in reinforcement learning (RL), active learning, Bayesian decision theory, and stochastic optimisation for partially observed and evolving systems. Key research directions include:
- Adaptive data acquisition strategies that maximise information gain under resource constraints;
- RL-based approaches for sequential intervention and control;
- Robust learning methods that adapt to incomplete observations, changing environments, and distributional shifts.
The research will combine probabilistic modelling, network-based representations, and modern AI methods to enable scalable and interpretable decision-making in complex systems. Applications will include adaptive disease surveillance, outbreak monitoring, resource allocation, and intervention planning using dynamic mobility and contact networks as motivating examples. The methodological contributions have broader relevance to sequential optimisation and decision-making problems across AI and data science.
The ideal candidate will have foundational knowledge of machine learning and strong self-motivation. You will be supervised by Dr. Mengyan Zhang, whose research focuses on sequential decision making and public health. Dr. Zhang has published in leading venues including Nature, PNAS, ICML, AAAI, etc. She collaborates widely through the Machine Learning and Global Health network, including with researchers at the University of Oxford, Imperial College London, and the National University of Singapore.
Candidate requirements: Funding: 4 year University Scholarship starting 2027/28 academic year. Minimum tax-free stipend at the current UKRI rate (for 2025/26 standard stipend is £20,780, RTSG £8,400, full Tuition Fee covered).
PhD Studentship: Learning and Decision-Making Under Uncertainty in Public Health employer: University of Bristol
Join our award-winning university health service as a Nurse Practitioner, where you will be part of a close-knit and supportive primary care team dedicated to the well-being of our diverse student population. Enjoy a collaborative work culture that fosters professional growth, with opportunities to engage in evidence-based patient care in a beautiful, purpose-built practice. We value your expertise and enthusiasm for working with young people, offering a fulfilling environment that prioritises both personal and professional development.
