项目介绍

2021年8月12日

Overview

The demand for numerate graduates exceeds the supply in most areas. Many new and existing opportunities – in industry, medicine, government, commerce, or research – await science graduates who have supplemented their first degree with additional training in quantitative skills, such as those provided by the postgraduate programmes available within the Department of Statistical Science.

Research areas

The department’s methodological research is organised into six themes:

• Biostatistics
• Computational statistics
• Economics, finance and business
• General theory and methodology
• Multivariate and high dimensional data
• Stochastic modelling and time series

Research often cuts across these themes. For example, externally funded projects in the following application areas are in progress:

• Cognitive neuroscience
• Ecology
• Econometrics and finance
• Epidemology
• Environmetrics and hydrology
• Machine learning
• Population and systems biology
• Statistical imaging

Much of this work is interdisciplinary and involves collaborations within and outside UCL.More information can be found on the department website: Statistical Science MPhil/PhD

About this degree

Additional costs

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs.

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble accessable.co.uk. Further information can also be obtained from the UCL Student Support & Wellbeing team.

Funding

Research Council funding may be available for UK/EU nationals. Other funding opportunities may also be available. For details visit www.ucl.ac.uk/statistics/prospective-postgraduates/studentships

Scholarships relevant to this department are displayed below.

CSC-UCL Joint Research Scholarship

Value:Fees, maintenance and travel (Duration of programme)Eligibility:OverseasCriteria:Based on academic merit

UCL Research Opportunity Scholarship

Value:UK rate fees, a maintenance stipend, conference costs and professional development package (3 years)Eligibility:UKCriteria:Based on both academic merit and financial need

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

Careers

Graduates of the PhD programme are well placed to continue as researchers in both academia and the private sector. In particular, greater data collection has created a demand for enhanced methodologies for analysis, which is a strength of most recent graduates.

Networking

The department has strong connections with a number of inter-disciplinary research organisations (for example the UCL Centre for Computational Statistics and Machine Learning (CSML), the UCL Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX), the Centre for Doctoral Training in Financial Computing & Data Science, the UCL Energy Institute, and the Alan Turing Institute). Staff members also collaborate directly with hospitals, power companies, government regulators, and the financial sector. Consequently, research students have ample opportunity to engage with external institutions in order to frame their work.

Why study this degree at UCL?

While the department offers world-class expertise along with strong links to practitioners, its position within UCL provides breadth. Besides ties to other mathematical sciences, the department collaborates with researchers in engineering, management, and medicine. The opportunity to engage with leading researchers across disciplines while accessing London-based government and industry figures gives UCL students a distinct advantage.

More intangibly, by being in a truly multidisciplinary environment, UCL students gain an appreciation for knowledge and its societal impact. This leads not only to new insights but also to a readiness to critique the established order, which is both intellectually and personally fulfilling.

Department: Statistical Science

What our students and staff say

Staff review

“UCL has an amazing portfolio of research. As a statistician I get to play with data from many different fields, which is exciting. Collaborating with other scientists at UCL enables me to contribute to a wide array of scientific disciplines.”

PROFESSOR SOFIA OLHEDE

Statistical Science MPhil/PhD
Professor of StatisticsStaff review

“UCL has always had a reputation for encouraging thought that is both unorthodox yet somehow addresses social concerns. Furthermore, UCL is a genuinely interdisciplinary institution in one of the world’s most diverse cities. My research, by nature, is interdisciplinary because of the various quantitative tools that I need to apply, for example, statistics for modelling energy prices and economics for capturing the behaviour of stakeholders. “

DR AFZAL SIDDIQUI

I am the Departmental Graduate Tutor with responsibility for the admission of post-graduate research students. I also supervise M.Sc. projects depending upon student interest.
Departmental Graduate TutorStudent review

“UCL is a great university for doing research, the PhD programmes here are well structured and there are many opportunities for personal development. Also, UCL offered me a scholarship for my postgraduate studies including a two-year research visit to the Agency for Science, Technology and Research (ASTAR) in Singapore.”

MARIA TOOMIK

Statistical Science PhD

Application and next steps

Applications

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

This programme requires two references. Further information regarding references can be found in our How to apply section.

Application deadlines

All applicants30 July 2021

Deadlines and start dates are usually dictated by funding arrangements so check with the department or academic unit to see if you need to consider these in your application preparation. In most cases you should identify and contact potential supervisors before making your application. For more information see our How to apply page.

For more information see our Applications page.

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