Data-adaptive sequential inference via differentiable particle filters
This project explores the intersection between machine learning and sequential Monte Carlo methods for data-adaptive sequential inference tasks with accurate uncertainty prediction.
Start date
1 October 2023Duration
36 monthsApplication deadline
Funding source
University of SurreyFunding information
Full tuition fee cover, stipend of c £17,000 p.a. and a £3,000 Research Training Support Grant.
About
Sequential inference is a key task in many of the everyday artificial intelligence (AI) and data science applications such as target tracking. Particle filters are a family of flexible algorithms using Bayesian Monte Carlo methods for sequential inference, by sequentially updating the probability distribution of internal states of a dynamic system from noisy measurements.
This project will leverage artificial neural networks to automatically build various components of particle filters. Replacing heuristic models in particle filters with data-driven ones would make them an extremely powerful tool in a wide range of real-world applications ranging from robotics and financial modelling.
Supervisors
Additional notes
Please note that this studentship award is part of a wider studentship competition. Those successful in being shortlisted will be put forward to a central panel consisting of University of Surrey and University of Wollongong staff who will then assess the applications and select four of the nominated candidates for funding.
Eligibility criteria
Open to UK and international candidates.
A Bachelor’s degree or above in computer science, electrical engineering, statistics, mathematics, physics or similar (a first class or the equivalent from an overseas university).
Past research experience with prior publications is preferable although not essential.
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. In place of a research proposal you should upload a document stating the title of the project that you wish to apply for, the name of the relevant supervisor and a personal statement. The statement should explain how your previous experience has prepared you for doctoral research and this project in particular. Explain how this PhD will support your career aspirations (maximum 500 words).
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