QM Principal Studentship: Probabilistic Programming, without Sampling

Probabilistic programming is a recent and extremely dynamic field of research which lies at the intersection of statistical machine learning and programming language theory. Probabilistic programming languages (e.g. Pyro, PyMC3, Anglican, …) are designed to make both the development of statistical models and the learning of their parameters as easy as possible. These languages have led to many new and interesting problems. How can we interpret probabilistic programs? How can we verify their correctness? How can they be evaluated efficiently?

A standard way of performing computations in a probabilistic program is to generate lots of samples, apply operations to these samples, and then plot a histogram which approximates the output distribution we are interested in. This approach is fast and intuitive but converges very slowly to the target distribution and, being only approximate, is unsuited to formal verification tasks. This project aims to develop another approach where probabilistic programs operate directly on distributions, rather than on samples. Concretely, this means developing (i) a probabilistic programming language which manipulates probability distributions, (ii) new algorithms to concretely evaluate programs written in this language, and (iii) the mathematical toolbox to interpret and verify them.

For more information about the project, please contact Fredrik Dahlqvist (f.dahlqvist@qmul.ac.uk).

Studentship

The PhD student will be supported by a QM Principal Studentship. They will receive tuition fees and a London stipend at UKRI rates (currently in 2023/34 of £20,662 per year, to be confirmed for 2024/25) annually during the PhD period, which can span for 3 years.

How to apply 

Queen Mary is interested in developing the next generation of outstanding researchers and decided to invest in specific research areas.  For further information about potential PhD projects and supervisors please see the list of the projects at the end of this page.

Applicants should work with their prospective supervisor and submit their application following the instructions at: http://eecs.qmul.ac.uk/phd/how-to-apply/  

The application should include the following: 

• CV (max 2 pages)
• Cover letter (max 4,500 characters) stating clearly in the first page whether you are eligible for a scholarship as a UK resident (https://epsrc.ukri.org/skills/students/guidance-on-epsrc-studentships/eligibility)
• Research proposal (max 500 words)
• 2 References
• Certificate of English Language (for students whose first language is not English)
• Other Certificates

Please note that to qualify as a home student for the purpose of the scholarships, a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship.  For more information please see: (https://epsrc.ukri.org/skills/students/guidance-on-epsrc-studentships/eligibility)  

Application Deadline 

The deadline for applications is the 1^st June 2024. 

For general enquiries contact Mrs Melissa Yeo at m.yeo@qmul.ac.uk (administrative enquiries) or Dr Arkaitz Zubiaga at a.zubiaga@qmul.ac.uk (academic enquiries) with the subject “EECS 2024 PhD scholarships enquiry”. 

For specific enquiries contact Dr Fredrik Dahlqvist – f.dahlqvist@qmul.ac.uk