About the Department of Pure Mathematics and Mathematical Statistics
The Department of Pure Mathematics and Mathematical Statistics (DPMMS) is one of two Mathematics Departments at the University of Cambridge, the other being the Department of Applied Mathematics and Theoretical Physics (DAMTP). The two departments together constitute the Faculty of Mathematics, and are responsible for the teaching of Mathematics and its applications within the Mathematical Tripos. The Statistical Laboratory is a sub-department of DPMMS.
3 courses offered in the Department of Pure Mathematics and Mathematical Statistics
Mathematics (Mathematical Statistics) - MASt
This course is the Mathematical Statistics stream of the Master of Advanced Study (MASt) in Mathematics; students should apply to only one of the four application streams for the MAst (Applied Mathematics, Pure Mathematics, Mathematical Statistics, or Theoretical Physics).
This course, commonly referred to as Part III, is a nine-month taught masters course in mathematics. It is excellent preparation for mathematical research and it is also a valuable course in mathematics and its applications for those who want further training before taking posts in industry, teaching, or research establishments.
Students admitted from outside Cambridge to the Part III are admitted to the Master of Advanced Study (MASt). Cambrdige students continuing from the Cambridge Mathematical Tripos for a fourth-year are admitted to the Master of Mathematics (MMath). The requirements and course structure for MASt and the MMath are the same.
Mathematics (Pure Mathematics) - MASt
This course is the Pure Mathematics stream of the Master of Advanced Study (MASt) in Mathematics; students should apply to only one of the four streams for the MAst (Applied Mathematics, Pure Mathematics, Mathematical Statistics, or Theoretical Physics).
This MAst, commonly referred to as Part III, is a nine-month taught masters course in mathematics. It is excellent preparation for mathematical research and it is also a valuable course in mathematics and its applications for those who want further training before taking posts in industry, teaching, or research establishments.
Students admitted from outside Cambridge to the Part III are admitted to the Master of Advanced Study (MASt). Cambrdige students continuing from the Cambridge Mathematical Tripos for a fourth-year are admitted to the Master of Mathematics (MMath). The requirements and course structure for MASt and the MMath are the same.
Pure Mathematics and Mathematical Statistics - PhD
This course is a three to four-year programme culminating in the submission and examination of a single research thesis. Students joining the course will often have completed prior study at a level comparable to our Part III (MMath/MASt) course and many have postgraduate experience. Our students, therefore, begin their PhD research with a good understanding of advanced material, which they build on in various ways throughout the course of their PhD studies. Our PhD students might have written several papers before they submit their thesis, and can go on to win academic positions at leading institutions around the world.
4 courses also advertised in the Department of Pure Mathematics and Mathematical Statistics
Biological Sciences - PhD - Closed
From the School of the Biological Sciences
The Cambridge Biosciences DTP is a four year fully-funded PhD programme that aims to create highly skilled and employable people. The programme offers training across 23 University Departments/Institutes and 3 Partner Institutes providing access to a wide range of research areas related to the strategic themes of the BBSRC. We offer three types of DTP studentships:
- DTP Standard
- Targeted
- iCase
During the programme, DTP Standard and Targeted students will undertake two ten-week rotations in different labs before commencing their PhD. They will receive training in a variety of areas including but not limited to statistics, programming, ethics, data analysis, scientific writing and public engagement. Students will also undertake a 12-week internship (PIPS).
iCase students are not required to undertake rotations but may do so if they feel that this training would be useful. They must undertake a placement with their Industrial Partner for a minimum of three months and a maximum of 18 months.
Students will be expected to submit their thesis at the end of the fourth year.
Part-time study, whilst not the norm, may be viable, depending on the project, and will be considered on a case by case basis so please discuss this option with your proposed supervisor before making an application for this mode of study.
Computational Methods for Materials Science CDT - MPhil + PhD
From the Department of Physics
The development of new materials lies at the heart of many of the technological challenges we currently face, for example creating advanced materials for energy generation. Computational modelling plays an increasingly important role in the understanding, development and optimisation of new materials.
This four-year doctoral training programme on computational methods for material modelling aims to train scientists not only in the use of existing modelling methods but also in the underlying computational and mathematical techniques. This will allow students to develop and enhance existing methods, for instance by introducing new capabilities and functionalities, and also to create innovative new software tools for materials modelling in industrial and academic research.
The first year of the doctoral training programme is provided by the existing MPhil course in Scientific Computing, which has research and taught elements, as well as additional training elements. The final three years consist of a PhD research project, with a student-led choice of projects offered by researchers closely associated with the CDT. (https://ljc.group.cam.ac.uk)
Mathematics - MPhil
From the Department of Applied Mathematics and Theoretical Physics
The MPhil is offered by the Faculty of Mathematics as a full-time period of research and introduces students to research skills and specialist knowledge. Its main aims are:
- to give students with relevant experience at first-degree level the opportunity to carry out focused research in the discipline under supervision; and
- to give students the opportunity to acquire or develop skills and expertise relevant to their research interests.
Scientific Computing - MPhil
From the Department of Physics
The MPhil programme in Scientific Computing provides world-class education on high performance computing and advanced algorithms for numerical simulation at continuum and atomic-scale levels. The course trains early-career scientists in the use of existing computational software and in the underlying components of the simulation pipeline, from mathematical models of physical systems and advanced numerical algorithms for their discretisation, to object-oriented programming and methods for high-performance computing for deployment in contemporary massively parallel computers. As a result, course graduates have rigorous research skills and are formidably well-equipped to proceed to doctoral research or directly into employment. The highly transferable skills in algorithm development and high-performance computing make our graduates extremely employable in all sectors of industry, commerce and finance.
The MPhil in Scientific Computing is suitable for graduates from any discipline of natural sciences, technology or engineering, who have good mathematical and computational skills.