Partner Universities
University of Cambridge
The University of Cambridge is one of the world’s oldest universities and leading academic centres, and a self-governed community of scholars. Its reputation for outstanding academic achievement is known worldwide and reflects the intellectual achievement of its students, as well as the world-class original research carried out by the staff of the university and the colleges. The University of Cambridge’s mission is to contribute to society through the pursuit of education, learning and research at the highest international levels of excellence.
The Departments
The Maths Department
The Faculty of Mathematics comprises two closely linked departments: the Department of Applied Mathematics and Theoretical Physics (DAMTP) and the Department of Pure Mathematics and Mathematical Statistics (DPMMS).
The University of Cambridge has been a world leader in mathematics for centuries and has taught and hosted some of the most influential mathematical minds in history, including Isaac Newton, Philippa Fawcett, Srinivasa Ramanujan, Mary Cartwright, Alan Turing, Stephen Hawking, and currently Sir Timothy Gowers.
As a faculty it is committed to providing an environment that nurtures and educates mathematicians at every stage of their academic career. It recruits some of the best students from the UK and across the world, and it provides undergraduate and postgraduate training of the highest international calibre.
It offers courses that provide deep fundamental understanding and broad exposure to the subject and its applications, enabling students to develop their problem-solving abilities and capacity for independent study. In doing so, it equips them for exciting careers in mathematical research, industry and the public sector.
Partnership with St John’s College
The Martingale Foundation, Faculty of Mathematics and St John’s College have partnered to ensure that students admitted via the Martingale Scholars Programme will typically have the option to be admitted as members of St John’s College and become part of a Martingale Scholars Cohort. If you would like more information on this partnership, please contact the Faculty directly.
Department of Computer Science and Technology
The Department of Computer Science and Technology is an academic department within the University of Cambridge that encompasses Computer Science, along with many aspects of Technology, Engineering and Mathematics.
The Department undertakes research in a broad range of subjects. It has an open and collaborative culture, supporting revolutionary fundamental computer science research, strong cross-cutting collaborations internally and externally, and ideas which transform computing outside the University. Current research areas include bioinformatics, computer architecture, computer vision, distributed systems, graphics and human-computer interaction, logic and semantics, machine learning, natural language processing, networking and wireless communication, operating systems and virtualization, programming, security, and sustainable computing.
Department of Engineering
The Department of Engineering is one of the few truly integrated engineering departments in the world. It is also the largest department in the University of Cambridge. Its breadth and scale bring unique advantage. The research portfolio develops pinnacles of world-class excellence, which adapt and combine to address a vast array of engineering challenges. Postgraduate teaching brings students into the heart of the latest research and developments. The undergraduates gain a strong foundation in all engineering disciplines together with in-depth knowledge of their chosen specialist field. Across research, teaching and postgraduate study, the Department of Engineering offers all its staff, students and industry partners a highly networked community for sharing and developing engineering knowledge.
Department of Physics
The Department of Physics, founded as the Cavendish Laboratory in 1874, has always been at the forefront of discovery in physics. The core of the Laboratory’s programme is experimental physics, supported by excellence in theory. The policy of the Department is to promote world-leading experimental and theoretical physics in all its diversity. Much of our research and teaching has been driven by the desire to understand physics at its most basic level, but equally challenging is research in other cognate disciplines where physics can make innovative and paradigm-changing contributions. All these research areas attract many of the world’s brightest students who relish the opportunity to tackle some of the toughest intellectual and experimental challenges in the whole of science.
The Masters courses offered through Martingale
Mathematical Sciences
MASt in Mathematics or MMath in Mathematics
These courses, which are commonly referred to as Part III, are both nine-month taught Masters courses in mathematics. Part III provides excellent preparation for mathematical research and is also a valuable course in mathematics and its applications for students who want further training before taking posts in industry, research or teaching establishments.
Each year the faculty offers up to 80 lecture courses in Part III, covering an extensive range of pure mathematics, probability, statistics, applied mathematics and theoretical physics. These are designed to cover advanced parts of the subjects that are not normally covered in a bachelor’s course, but which are an indispensable preliminary to independent study and research. Students can choose various combinations of courses, although naturally they tend to select groups of cognate courses. Example classes and associated marking of example sheets are provided as complementary support to lectures.
MPhil in Mathematics
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: (i) to give students with relevant experience at first-degree level the opportunity to carry out focused research in the discipline under supervision; and (ii) to give students the opportunity to acquire or develop skills and expertise relevant to their research interests.
This is a 12-month full-time programme and involves minimal formal teaching: students are integrated into the research culture of the Department of Pure Mathematics & Mathematical Statistics (DPMMS), or the Department of Applied Mathematics and Theoretical Physics (DAMTP), as appropriate. They may attend the Departments’ programmes of research seminars and other postgraduate courses, but most research training is overseen by their research supervisor, and, where appropriate, within a research group. Opportunities to develop research and transferable skills also exist through attendance at training sessions organised at Department, School or University level as part of the wider postgraduate programme, and informally through mentoring by fellow students and members of staff.
Artificial Intelligence
MPhil in Advanced Computer Science
The aim of this 9-month course is to develop research skills and methodology in computer science. Students select five taught modules from a wide range of advanced topics in computer science from networking and systems measurements to category theory, and topics in natural language processing, alongside an independent research project. The taught modules are delivered in a range of styles: traditional lecture courses, lecture courses with associated practical classes, reading clubs, and seminar style modules. Additionally, students take an ungraded course in research skills which includes core and optional topics.
MPhil in Machine Learning and Machine Intelligence
This 11-month course has a unique joint emphasis on both machine learning and machine intelligence. The course is split into four specialised pathways, which set the scope for the dissertation, and which each have different module combinations. The four pathways are: (i) Machine Learning; (ii) Speech and Language Processing; (iii) Computer Vision and Robotics; (iv) Human-Computer Interaction. The course aims to teach the state of the art in machine learning and machine intelligence; to give students the skills and expertise necessary to take leading roles in industry; and to equip students with the research skills necessary for doctoral study.
MPhil in Scientific Computing
This 12-month course aims to introduce students to research skills and specialist knowledge. The course provides world-class education on high performance computing and advanced algorithms for numerical simulation at continuum and atomic-scale levels. Its main aims are to:
- encourage and pursue research of the highest quality in Scientific Computing and its applications.
- provide education in Scientific Computing of the highest quality at a postgraduate level and to produce graduates of the calibre sought by industry, the professions, and the public service.
- provide training for the academic researchers and teachers of the future.
MPhil in Data Intensive Science
This 10-month course prepares science graduates for data intensive research careers by providing advanced training in Statistical Analysis, Machine Learning, and Research Computing, and their application to current research frontiers. The course aims to:
- train exceptional research scientists to design and implement data analysis pipelines for increasingly complex data sets;
- enable development of data science skills which can be applied in science, health and economic areas;
- train students in data science techniques and algorithm building for modern computer architectures and software development;
- increase availability of open science, specifically reproducibility of results and the creation of public data analytic codes.
The PhD courses offered through Martingale
PhD in Applied Mathematics and Theoretical Physics
This is a three to four-year research programme culminating in submission and examination of a thesis containing substantial original work. PhD students carry out their research under the guidance of a supervisor, and research projects are available from a wide range of subjects studied within the Department.
Students admitted for a PhD will normally have completed preparatory study at a level comparable to the Cambridge Part III (MMath/MASt) course. A significant number of these PhD students secure post-doctoral positions at institutions around the world and become leading researchers in their fields.
Find out more here.
PhD in Pure Mathematics and Mathematical Statistics
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 the Part III (MMath/MASt) course and many have postgraduate experience. 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.
Research in DPMMS can be divided into the following broad areas: Algebra, Algebraic Geometry, Analysis and Partial Differential Equations, Combinatorics, Differential Geometry and Topology, Number Theory, Information and Finance, Probability, and Statistics. The boundaries between such areas are not rigid, however, and staff may contribute to more than one area.
Find out more here.