Statistical Science MPhil/PhD


Research areas:

The department’s methodological research is organised into six areas:
  • Biostatistics
  • 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
  • Ecology
  • Econometrics and finance
  • Epidemology
  • Environmetrics and hydrology
  • Machine learning
  • Population and systems biology
  • Statistical imaging
  • Stochastic optimisation in the energy sector
Much of this work is interdisciplinary and involves collaborations within and outside UCL.

IRIS logo

Visit the IRIS research portal to learn more about researchers' activities, research groups, research centres and interdisciplinary networks across the whole of UCL.

IRIS department: Dept of Statistical Science


Entry requirements

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 level expected: Standard

Application

Research degrees may start at any time of the year, but typically start in September. Deadlines and start dates are usually dictated by funding arrangements so check with the department or academic unit (contact listed in Next steps, right) 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.

Fees

  • UK/EU Full-time: £4,500
  • UK/EU Part-time: £2,250
  • Overseas Full-time: £16,200
  • Overseas Part-time: £8,250

Funding

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

Scholarships available for this department

CSC-UCL Joint Research Scholarship

Funding offered by UCL and the China Scholarships Council (CSC) aims to expand the educational, cultural and technological cooperation between the UK and China.

Full details of funding opportunities can be found on the UCL Scholarships website


Career

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.

Top career destinations for this programme

  • University of Salerno, Lecturer, 2009
  • Medical Research Council, Medical Statistician, 2009
  • UCL, Research Associate, 2010
  • Norwegian School of Economics, Assistant Professor, 2011
  • Nottingham Trent University, Lecturer, 2008

Networking

The department has strong connections with inter-disciplinary research institutes at UCL (e.g. the Centre for Computational Statistics and Machine Learning (CSML), the Centre for Mathematics and Physics int he Life Sciences and Experimental Biology (CoMPLEX), the UK PhD Centre in Financial Computing and the Energy Intitute), which interface regularly with the public and private sectors. Stafg 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.


Next steps

Contact

Department

Statistical Science

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Staff View

"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

Professor of Statistics

Student View

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Rodrigo Targino

Degree: Statistics PhD