The automation of manufacturing and service sectors is facilitated by advances in computing; however, this transition towards data-driven decision-making requires more sophisticated use of statistics. Analysing larger volumes of data creates both challenges that can be addressed by existing statistical methods and also opportunities for the development of novel algorithms.
Modes and duration
Tuition fees (2018/19)
- £5,060 (FT) £2,530 (PT)
- £21,440 (FT) £10,740 (PT)
Note on fees: The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Current Students website.
A minimum of an upper second-class UK Bachelor's degree, or a UK Master's degree in statistics, mathematics, computer science or a related quantitative discipline. Overseas qualifications of an equivalent standard are also acceptable.
English language requirements
If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.
The English language level for this programme is: Standard
Further information can be found on our English language requirements page.
Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.
International applicants can find out the equivalent qualification for their country by selecting from the list below.
Select your country:
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.
The department’s methodological research is organised into six areas:
- Computational statistics
- General theory and methodology
- Multivariate and high dimensional data
- Stochastic modelling and time series
- Financial risk, insurance, econometrics and stochastic finance
Research often cuts across these areas. For example, externally funded projects in the following application areas are in progress:
- Cognitive neuroscience
- Econometrics and finance
- Environmetrics and hydrology
- Machine learning
- Population and systems biology
- Statistical imaging
Much of this work is interdisciplinary and involves collaborations within and outside UCL.
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.
- Now closed for 2018/19.
- Fees, maintenance and travel (Duration of programme)
- Based on academic merit
For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.
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.
Recent career destinations for this degree
- Post-Doctoral Research Associate, Medical Research Council
- Post-Doctoral Research Associate, University of Cambridge
- Quantitative Analyst, Gazprom Marketing & Trading
- Associate, Goldman Sachs
- Quantitative Analyst, Barclays
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 & Analytics, 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.
Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.
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
Student / staff numbers
› 36 staff
Staff/student numbers information correct as of 1 August 2017.
Research Excellence Framework (REF)
The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.
The following REF score was awarded to the department: Statistical Science
82% rated 4* (world-leading) or 3* (internationally excellent)
Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.
What our students and staff say
"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 OlhedeStatistical Science MPhil/PhD
Professor of Statistics
"UCL is one of the leading universities worldwide. In particular, I like that statistics is a department on its own and not, as is often the case, part of mathematics. Therefore, the research areas in statistics investigated in our department cover a huge variety. As a PhD student, I find it very important to be exposed to more than only your own field of research."
Beate FrankeStatistical Science PhD
"After deciding to pursue my graduate studies in London (due to countless opportunities for industry collaborations) choosing UCL as a university was not hard. I was looking for a statistics department where I could be exposed to as many different research areas as possible and UCL Statistical Science could offer me this opportunity. Of course, studying in the first statistics department in the world also has its charm."
Rodrigo TarginoStatistical Science PhD
Application and next steps
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.
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.Apply now