Machine learning meets sequential Monte Carlo methods

The project develops computationally efficient statistical tools to express model uncertainty in sequential prediction tasks.

Start date
1 January 2023
3.5 years
Application deadline
Funding source
EPSRC NPL iCASE studentship
Funding information
  • UK tuition fees
  • Enhanced UKRI stipend at £19,062 p.a. (2022/23 rate)
  • Research Training Support at £1,000 p.a.
  • Personal Computer (provided by the Department).


This project lies on the intersection of modern machine learning techniques and sequential Monte Carlo methods. Sequential Monte Carlo (SMC) methods, e.g. particle filters, are a class of powerful simulation-based algorithms to utilise data uncertainty and generate model uncertainty.

Replacing the heuristic models in SMC by data-driven ones through the incorporation of machine learning will make them an extremely powerful tool in real-world applications including computer vision, finance, object tracking and robotics. This project will develop innovate statistical methods and apply the developed techniques in large-scale real-world datasets.

Later start dates possible: October 2022, January 2023, April 2023, July 2023.

Related links
EUSIPCO 2022 Special Session on Machine Learning for Sequential Monte Carlo Met…
Additional notes

The application is rolling-based with no fixed submission deadline until the position is filled. Early applications are strongly encouraged for early PhD start. The PhD student will be based at the Nature Inspired Computing and Engineering (NICE) research group in the Department of Computer Science at the University of Surrey. The student will also benefit from ample computing and research resources from Centre for Vision, Speech and Signal Processing (CVSSP) and the Surrey Institute for People-Centred AI.

Eligibility criteria

A Bachelor’s degree or above in Computer Science, Electrical Engineering, Statistics, Mathematics, Physics or similar (a First Class or good Upper Second Class Honours degree, or the equivalent from an overseas university).

English languages requirements

IELTS minimum 6.5 overall with minimum 6.0 in each component, or equivalent.

How to apply

Applications should be submitted via the Computer Science PhD programme page on the "Apply" tab. Please clearly state the studentship title and supervisor on your application.

Application deadline

Contact details

Yunpeng Li
14 BB 02
Telephone: +44 (0)1483 682626

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