Scalable Intelligent Planning for Partially Observable Uncertain Systems University of Bristol in United Kingdom

The University of Bristol's School of Engineering Mathematics and Technology is offering a PhD position focused on scalable intelligent planning for partially observable uncertain systems. Modern infrastructure, including power grids, water networks, and transportation systems, relies on sustainable and continuous operation. However, these 'systems of systems' are complex, nonlinear, and often stochastic, making their management a significant scientific and logistical challenge. Small local failures can lead to cascading effects, and monitoring their status is difficult due to partial observability and uncertainty in data.

This project aims to develop scalable methodologies for adaptive prioritization of inspection and maintenance actions in large-scale infrastructure systems. The research will address the trade-offs inherent in maintenance decisions, balancing resource allocation and system availability. The successful candidate will engage in nonlinear modelling, stochastic process analysis, and the application of machine learning and control systems to real-world infrastructure challenges.

Applicants should have a strong academic background in mathematics, engineering, or computer science, with demonstrated analytical rigor and motivation to apply theoretical advances to practical problems. The project is supervised by Dr KZ Zhang and is based at the University of Bristol, a leading UK institution renowned for its research in systems engineering and technology.

Funding details are not specified in the position description. The application deadline is February 28, 2027. Interested candidates should apply online via the provided project link and prepare a CV and cover letter highlighting their relevant experience and motivation. For further information, applicants may contact the supervisor directly.