Semi-supervised learning for regression

We are recruiting new Doctoral Researchers to our EPSRC funded Doctoral Training Partnership (DTP) PhD studentships starting 1 October 2024. Applications are invited for the project title Semi-supervised learning for regression. Successful applicants will receive an annual stipend (bursary) of £21,237, including inner London weighting, plus payment of their full-time home tuition fees for a period of 42 months (3.5 years).

You should be eligible for home (UK) tuition fees there are a very limited number (no more than three) of studentships available to overseas applicants, including EU nationals, who meet the academic entry criteria including English Language proficiency.

You will join the internationally recognised researchers in the Department of Mathematics research and PhD programmes | Brunel University London

The Project

While both supervised and unsupervised techniques dominate the field of machine learning, the term "semi-supervised learning" describes a scenario in which some data is labeled, while the remainder is unlabeled. Such situations arise when observing the label variable proves challenging and may necessitate a complex or costly procedure. An illustrative example is web document classification, where human agents handle the classification of a subset, while numerous other online documents remain unlabeled.

Semi-supervised learning is a relatively recent but burgeoning area in statistics, machine learning, and data analytics. This project aims to provide comprehensive training for a proficient Ph.D. student in this domain, focusing on the development of new methods or making innovative contributions with certain regression models within the field.

Please contact Professor Keming Yu at keming.yu@brunel.ac.uk for an informal discussion about the studentships.

Eligibility

Applicants will have or be expected to receive a first or upper-second class honours degree in an Engineering, Computer Science, Design, Mathematics, Physics or a similar discipline. A Postgraduate Masters degree is not required but may be an advantage.

Skills and Experience

Applicants will be required to demonstrate the following skills and abilities to:

show his/her strong background on Statistical theory (including asymptotic theory or large sample theory) , Regression models and methods or/and Machine learning
have good experience in using R or Python for simulation and data analysis
motivate highly and work independently as well as in a team, collaborate
have good communication skills.

How to apply

There are two stages of the application:

1.Applicants must submit the pre-application form via the following link

https://brunel.onlinesurveys.ac.uk/epsrc-dtp-24-25-pre-application-form-brunel-university-lon

by 16.00 on Friday 5th April 2024.

2.If you are shortlisted for the interview, you will be asked to email the following documentation in a single PDF file to cedps-studentships@brunel.ac.uk within 72hrs.

Your up-to-date CV;
Your Undergraduate degree certificate(s) and transcript(s) essential;
Your Postgraduate Masters degree certificate(s) and transcript(s) if applicable;
Your valid English Language qualification of IELTS 6.5 overall (minimum 6.0 in each section) or equivalent, if applicable;
Contact details for TWO referees, one of which can be an academic member of staff in the College.

Applicants should therefore ensure that they have all of this information in case they are shortlisted.

Interviews will take place in April/May 2024.

Meet the Supervisor(s)

Keming Yu - Keming Yu – Chair in Statistics Impact champion of REF – in UOA (Mathematical Sciences) Keming joined Brunel University London in 2005. Before that he held posts at various institutions, including University of Plymouth, Lancaster University and the Open University. Keming got his first degree in Mathematics and MSc in Statistics from universities in China and got his PhD in Statistics from The Open University, Milton Keynes.