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School of Mathematical Sciences

Probability, Statistics and Data Science PhD Project

PhD projects in the Centre for Probability, Statistics and Data Science

The Centre for Probability, Statistics and Data Science covers three broadly overlapping main areas of research: probability, statistics and data science. Probability theory is a core topic within mathematics and a foundational aspect in much of the work of the centre. A broad range of areas within probability and applied probability are investigated from stochastic processes, understanding the properties of random mathematical structures including many applications to areas such as statistical physics, finance, etc. The centre also has a strong group of statisticians developing both statistical theory, e.g. Bayesian inference, methodologies, e.g. modelling of spatio-temporal data, and applications, e.g. biostatistics. Finally, the centre has in expertise of other aspects of data science including the foundations of machine learning, solving inverse systems as related to data, topological techniques, and others.  

The Centre also welcomes applications year-round from students with alternative sources of funding, such as self-funding, Doctoral Loans, Commonwealth scholarships, or other funding options. Contact the relevant academic to discuss projects alternatively if you are considering a PhD using funding not listed below, we encourage you to contact the relevant academic to discuss potential projects. 

The School of Mathematical Sciences invites applications for the PhD projects listed below in the Centre for Probability, Statistics and Data Science.

Each project includes information on eligible funding applicants, expected start dates, and submission deadlines.

All the projects below are open to applicants and will be considered on a rolling basis for interview and offer:

Funding:

-QMUL S&E Research Support Fund (RSF) 3yrs Home Fees and Stipend only – apply anytime by TBC – start date to be discussed with Supervisor 

Project:

- Mathematical foundations for AI - Supervisor: Prof Omer Bobrowski & Prof Primoz Skraba 

 

 

 

 

 

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