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 our PhD students secure post-doctoral positions at institutions around the world and become leading researchers in their fields.

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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. 

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This course is an application stream for the Master of Advanced Study (MASt) in Mathematics; students should apply to only one of the application streams for this course.

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 Part III study towards the Master of Advanced Study (MASt). Students continuing from the Cambridge Mathematical Tripos for a fourth-year study towards the Master of Mathematics (MMath). The requirements and course structure for Part III are the same for all students irrespective of whether they are studying for the MASt or MMath degree, or whether they applied through the Applied Mathematics (MASA), Pure Mathematics (MASP), Mathematical Statistics (MASS), or Theoretical Physics (MASTH) application stream.

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This course is an application stream for the Master of Advanced Study (MASt) in Mathematics; students should apply to only one of the application streams for this course.

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 Part III study towards the Master of Advanced Study (MASt). Students continuing from the Cambridge Mathematical Tripos for a fourth-year study towards the Master of Mathematics (MMath). The requirements and course structure for Part III are the same for all students irrespective of whether they are studying for the MASt or MMath degree, or whether they applied through the Applied Mathematics (MASA), Pure Mathematics (MASP), Mathematical Statistics (MASS), or Theoretical Physics (MASTH) application stream.

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The MPhil in Quantitative Climate and Environmental Sciences is a 10-month cross-departmental programme in the School of the Physical Sciences which aims to provide education of the highest quality in the analysis and modelling of Earth's climate and environment at a master’s level. The programme covers a range of skills required for the acquisition and assessment of laboratory and field data, and for the understanding through quantitative modelling of climate and environmental processes. 

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From the British Antarctic Survey

This PhD course takes place under the joint supervision of a research scientist at the British Antarctic Survey (BAS) and a University supervisor. Students may be based at BAS but will be registered for their degree with one of the partnering departments: Archaeology & Anthropology, Land Economy, Plant Sciences, Zoology, Earth Sciences, Geography and Scott Polar Research Institute, Applied Mathematics & Theoretical Physics, Chemistry, Engineering, Computer Science and Technology.

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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.

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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) 

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From the Department of Physics

The MPhil in Data Intensive Science is a 10-month cross-departmental programme in the School of the Physical Sciences which aims to provide education of the highest quality at the master’s level. The programme covers the full range of skills required for modern data-driven science. The course covers material from the fields of machine learning and AI, statistical data analysis, research and high performance computing, and the application of these topics to scientific research frontiers.  

The course structure has been designed in collaboration with our leading researchers and industrial partners to provide students with the theoretical knowledge, practical experience, and transferable skills required to undertake world-leading data-intensive scientific research. Students will gain the broad set of skills required for scientific data analysis, covering traditional statistical techniques as well as modern machine learning approaches.  Both the theoretical underpinnings and practical implementation of these techniques will be taught, with the later aspect including training on software development best practice and the principles of Open Science. The course also aims to provide students with direct experience applying these methods to current research problems in specific scientific fields. Students who have completed the course will be equipped to undertake research on data-intensive scientific projects. Beyond academic disciplines, students will be well prepared for a career as a data science professional in a broad range of commercial sectors.

This course will equip students with all the skills required for modern scientific data analysis, enabling them to participate in large experimental or observational programmes using the latest statistical and machine learning tools deployed on leading-edge computer architectures. These computational and statistical skills will also be directly applicable to data-driven problem-solving in industry.

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From the Department of Pure Mathematics and Mathematical Statistics

From the Institute of Astronomy

The MPhil in Planetary Sciences and Life in the Universe is a 10-month cross-departmental programme designed to deliver outstanding postgraduate level training in the search for life’s origins on Earth and its discovery on planets beyond Earth.

The course structure has been designed by leading scientists to provide students with the theoretical knowledge, practical experience, and transferable skills required to undertake world-leading research in Planetary Sciences and Life in the Universe. Graduating students will be equipped with the discipline specific-specialisations and skills of a masters course, whilst gaining understanding in how the core areas that bridge PSLU fields form the cross-disciplinary foundation of this exciting new frontier.

Graduates of the course will gain valuable skills rooted in the study of the physics, chemistry, mathematics, and biology of planetary science and life in the universe. Transferrable skills training is delivered through the three group-based projects running over the year: these provide a unique opportunity for students to gain experience of leadership, collaboration, and written and oral communication.  The training provided will be an outstanding foundation for PhD research in planetary science, exoplanetary science, Earth system science, planetary astrophysics, astrobiology and allied disciplines, or for the wide range of careers where analytical skills, excellent communication, and experience of leading collaborations are key.

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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.  

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