Master

In Oxford

Price on request

Description

  • Type

    Master

  • Location

    Oxford

About the course
In the DPhil in Statistics, you will investigate a particular project in depth and write a thesis which makes a significant contribution to the field. You will acquire a wide range of research and transferable skills, as well as in-depth knowledge, understanding and expertise in your chosen field of research. You will become part of a vibrant community of researchers.

Facilities

Location

Start date

Oxford (Oxfordshire)
See map
Wellington Square, OX1 2JD

Start date

On request

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Subjects

  • Project
  • Supervisor
  • IT
  • Statistics
  • University

Course programme

The Department of Statistics in the University of Oxford is a world leader in research in probability, bioinformatics, mathematical genetics and statistical methodology, including computational statistics, machine learning and data science. Oxford’s Mathematical Sciences submission came first in the UK on all criteria in the 2014 Research Excellence Framework (REF) and in 2016 the department moved to a newly-refurbished building in the centre of Oxford.

Much of the department’s research is either explicitly interdisciplinary or draws its motivation from application areas, ranging from biology and physics to the social sciences. The department is also part of a number of Centres for Doctoral Training (CDT) which admit graduate students:

  • StatML (Modern Statistics and Statistical Machine Learning), an EPSRC CDT in applicable modern statistical theory and methods as well as on the underpinnings of statistical machine learning in association with Imperial College London;
  • Mathematics of Random Systems: Analysis, Modelling and Algorithms, an EPSRC CDT in the area of probabilistic modelling, stochastic analysis and their applications in association with Imperial and Oxford Mathematics; and
  • Sustainable Approaches to Biomedical Science (SABS), an EPSRC and MRC CDT focusing on quantitative and predictive research at the interface between the mathematical and physical, and the biological and medical sciences.

Initially, you will be admitted as a Probationer Research Student in the same way as those intending to do a MSc by Research. Thus, it may be possible to switch between the two. The same standards are applied for admission for the two degrees.

You will be assigned a named supervisor or supervisors, who will have overall responsibility for the direction of your work on behalf of the department. You will have the opportunity to interact with fellow students and other members of your research groups, and more widely across the department. Typically, as a research student, you should expect to have meetings with your supervisor or a member of the supervisory team with a frequency of at least once every two weeks averaged across the year. The regularity of these meetings may be subject to variations according to the time of the year, and the stage that you are at in your research programme.

There are formal assessments of progress on the research project at around 12 to 15 months and at around 30 to 36 months. These assessments involve the submission of written work and oral examination.

The final thesis is normally submitted for examination during the fourth year and is followed by the viva examination.

You will be expected to acquire transferable skills as part of your training, and to undertake a total of 100 hours broadening training outside your specialist area over the course of the DPhil. Part of that broadening training is obtained through APTS, the Academy for PhD Training in Statistics; this is a joint venture with a group of leading university statistics departments which runs four weeks of appropriate courses a year. You will give a research presentation or prepare a research poster each year in the department. There may also be opportunities to undertake industrial internships as appropriate.

You are expected to teach approximately 12 contact hours per year in undergraduate and graduate courses in the department. This is mentored teaching, beginning with simple marking, to reach a point where individual students are leading whole classes of 10 to 12 undergraduate students.

Supervision

The allocation of graduate supervision for this course is the responsibility of the Department of Statistics and it is not always possible to accommodate the preferences of incoming graduate students to work with a particular member of staff. Under exceptional circumstances, a supervisor may be found outside the Department of Statistics.

Graduate destinations

After research degrees, the majority of the department’s graduates move into research and academic careers. Others work, for example, in data analytics, in tech and biotech companies and in the financial sector.

Changes to this course and your supervision

The University will seek to deliver this course in accordance with the description set out in this course page. However, there may be situations in which it is desirable or necessary for the University to make changes in course provision, either before or after registration. In certain circumstances, for example due to visa difficulties or because the health needs of students cannot be met, it may be necessary to make adjustments to course requirements for international study.

Where possible your academic supervisor will not change for the duration of your course. However, it may be necessary to assign a new academic supervisor during the course of study or before registration for reasons which might include sabbatical leave, parental leave or change in employment.

For further information, please see our page on changes to courses.

Other courses you may wish to consider

If you're thinking about applying for this course, you may also wish to consider the courses listed below. These courses may have been suggested due to their similarity with this course, or because they are offered by the same department or faculty.

All graduate courses offered by the Department of Statistics

Mathematical Sciences MSc

Modern Statistics and Statistical Machine Learning EPSRC CDT

Statistical Science MSc

Statistical Science PGDip

Statistics DPhil

Statistics MSc by Research

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Entry requirements

Statistics

Price on request