With ongoing activities in areas like biological applications, statistical ecology, and nonparametric statistics, research students joining SMSAS will become part of a thriving and vibrant research community.
There's a well-established system of support and training, with a high level of contact between staff and research students. A very active research seminar programme further enhances the Statistics research experience.
These programmes offers the opportunity to begin or consolidate your research career under the guidance of internationally renowned researchers and professionals in the School of Mathematics, Statistics and Actuarial Science (SMSAS).
Research interests are diverse and include: Bayesian statistics; bioinformatics; biometry; ecological statistics; epidemic modelling; medical statistics; nonparametric statistics and semi-parametric modelling; risk and queueing theory; shape statistics.
Statistics at Kent provides:
- a programme that gives you the opportunity to develop practical, mathematical and computing skills in statistics, while working on challenging and important problems relevant to a broad range of potential employers
- teaching and supervision by staff who are research-active, with established reputations and who are accessible, supportive and genuinely interested in your work
- advanced and accessible computing and other facilities
- a congenial work atmosphere with pleasant surroundings, where you can socialise and discuss issues with a community of other students.
About the School of Mathematics, Statistics and Actuarial Science (SMSAS)
The School has a strong reputation for world-class research and a well-established system of support and training, with a high level of contact between staff and research students. Postgraduate students develop analytical, communication and research skills. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School. We encourage all postgraduate statistics students to take part in statistics seminars and to help in tutorial classes.
The Statistics Group is forward-thinking, with varied research, and received high rankings in the Research Excellence Framework (REF) 2014 for research power and quality.
In the Research Excellence Framework (REF) 2014, research by the School of Mathematics, Statistics and Actuarial Science was ranked 25th in the UK for research power and 100% or our research was judged to be of international quality.
An impressive 92% of our research-active staff submitted to the REF and the School’s environment was judged to be conducive to supporting the development of world-leading research.
The research interests of the group are in line with the mainstream of statistics, with emphasis on both theoretical and applied subjects.
There are strong connections with a number of prestigious research universities such as Texas A&M University, the University of Texas, the University of Otago, the University of Sydney and other research institutions at home and abroad.
The group regularly receives research grants. The EPSRC has awarded two major grants, which support the National Centre for Statistical Ecology (NCSE), a joint venture between several institutions. A BBSRC grant supports stochastic modelling in bioscience.
Kent’s Computing Service central facility runs Windows. Within the School, postgraduate students can use a range of UNIX servers and workstations. Packages available include R, SAS, MATLAB, SPSS and MINITAB.
Dynamic publishing culture
Staff publish regularly and widely in journals, conference proceedings and books. Among others, they have recently contributed to: Annals of Statistics; Biometrics; Biometrika; Journal of Royal Society, Series B; Statistics and Computing. Details of recently published books can be found within our staff research interests.
The taught programmes in Statistics and Statistics with Finance provide exemption from the professional examinations of the Royal Statistical Society and qualification for Graduate Statistician status.
Researcher Development Programme
Kent's Graduate School co-ordinates the Researcher Development Programme for research students, which includes workshops focused on research, specialist and transferable skills. The programme is mapped to the national Researcher Development Framework and covers a diverse range of topics, including subject-specific research skills, research management, personal effectiveness, communication skills, networking and teamworking, and career management skills.
Students often go into careers as professional statisticians in industry, government, research and teaching but our programmes also prepare you for careers in other fields requiring a strong statistical background. You have the opportunity to attend careers talks from professional statisticians working in industry and to attend networking meetings with employers.
Our graduates have started careers in diverse areas such as the pharmaceutical industry, financial services and sports betting.
A first or 2.1 in a relevant subject.
General entry requirements
All applicants are considered on an individual basis and additional qualifications, and professional qualifications and experience will also be taken into account when considering applications.
Please see our International Student website for entry requirements by country and other relevant information for your country.
Meet our staff in your country
For more advise about applying to Kent, you can meet our staff at a range of international events.
English language entry requirements
For detailed information see our English language requirements web pages.
Please note that if you are required to meet an English language condition, we offer a number of pre-sessional courses in English for Academic Purposes through Kent International Pathways.
Biometry and ecological statistics
Specific interests are in biometry, cluster analysis, stochastic population processes, analysis of discrete data, analysis of quantal assay data, overdispersion, and we enjoy good links within the University, including the School of Biosciences and the Durrell Institute of Conservation and Ecology. A recent major joint research project involves modelling the behaviour of yeast prions and builds upon previous work in this area. We also work in collaboration with many external institutions.
Current work includes non-parametric Bayes, inference robustness, modelling with non-normal distributions, model uncertainty, variable selection and functional data analysis.
Bioinformatics, statistical genetics and medical statistics
Research covers bioinformatics (eg DNA microarray data), involving collaboration with the School of Biosciences. Other interests include population genetics, clinical trials and survival analysis.
Research focuses on empirical likelihood, high-dimensional data analysis, nonlinear dynamic analysis, semi-parametric modelling, survival analysis, risk insurance, functional data analysis, spatial data analysis, longitudinal data analysis, feature selection and wavelets.
Staff research interests
Kent’s world-class academics provide research students with excellent supervision. The academic staff in this school and their research interests are shown below. You are strongly encouraged to contact the school to discuss your proposed research and potential supervision prior to making an application. Please note, it is possible for students to be supervised by a member of academic staff from any of Kent’s schools, providing their expertise matches your research interests. Use our ‘find a supervisor’ search to search by staff member or keyword.
Full details of staff research interests can be found on the School's website.
Dr Diana Cole: Senior Lecturer in Statistics
Branching processes in biology; cell division models; ecological statistics; generalised linear mixed models; identifiability.; parameter redundancy.Profile
Dr Alfred Kume: Senior Lecturer in Statistics
Shape analysis; directional statistics; image analysis.Profile
Dr Alexa Laurence: Lecturer in Statistics
Medical statistics and applied statistics.Profile
Dr Fabrizio Leisen: Senior Lecturer in Statistics
Bayesian nonparametrics; MCMC, Urn models; Markov and Levy processes; Move-to-Front and Move-to-Root allocation rules.Profile
Dr Owen Lyne: Lecturer in Statistics
Stochastic epidemic models; applied probability; simulation; statistical inference; goodness of fit; branching processes; martingales; medical education.Profile
Dr Rachel McCrea: Research Associate
Integrated population modelling of dependent data structures.Profile
Professor Byron Morgan: Professor of Applied Statistics
Biometry; cluster analysis; stochastic population processes; psychological applications of statistics; multivariate analysis; simulation; analysis of quantal assay data; medical statistics; ecological statistics; overdispersion; estimation using transforms.Profile
Professor Martin S Ridout: Professor of Applied Statistics
Analysis of discrete data in biology; generalised linear models; overdispersion; stochastic models; transform methods.Profile
Professor Jian Zhang: Professor of Statistics
Semi and non-parametric statistical modelling; statistical genetics with medical applications; Bayesian modelling; mixture models; neuroimaging.Profile
Dr Xue Wang: Lecturer in Statistics
Bayesian nonparametric methods; copula function with its applications in finance; wavelet estimation methods.Profile
Enquire or order a prospectus
T: +44 (0)1227 827272
T: 44 (0)1227 824133
We hold regular Open Events at our Canterbury and Medway campuses. You will be able to talk to specialist academics and admissions staff, find out about our competitive fees, discuss funding opportunities and tour the campuses.
You can also discuss the programmes we run at our specialist centres in Brussels, Athens, Rome and Paris at the Canterbury Open Events. If you can't attend but would like to find out more you can come for an informal visit, contact our information team or find out more on our website.
Please check which of our locations offers the courses you are interested in before choosing which event to attend.