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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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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The vision of this PhD programme is to deliver bespoke cohort-based interdisciplinary training which promotes holistic problem-focused thinking for nanoscientists, and drives new scientific directions as well as impactful, and responsible translation of research to technologies. A particular emphasis will be exposure to a broad range of world-class research environments, to allow students to discover their individual research and technology interests and develop strong ownership of their PhD topic.

The first six months of the programme will provide advanced-level training, specifically designed for students, through an integrated lectures + practicals module on Applied Nanoscience, a module on System Integration for Experimentalists and one short and one longer experimental project, prior to final selection of an interdisciplinary PhD research project between two research groups in the Departments of Physics, Chemistry, Engineering, Materials Science or another relevant department within the University. An additional module on Innovation for Scientists will help students develop a wider perspective, including training on innovation, sustainability and responsible research.

Throughout the programme there will be an environment supporting creativity, resilience, peer-to-peer learning, networking and connectivity. The programme will offer professional skills training to support students for different career paths in industry, academia and beyond, and will help students discover and nurture their leadership approach in varied contexts. Cross-cohort events will include student-led conferences, research seminars, onsite and offsite research and career development workshops led by internal and external experts and other activities.

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The MASt in Physics is a taught master's-level course in which students who applied from outside the University of Cambridge work alongside students taking the final year of the integrated undergraduate-and-master's course in Physics. This year is designed for students who wish to pursue a professional career in physics, (in academic or industrial research) and who are already familiar with the physics covered in a typical three-year UK bachelor's physics programme.

MASt students study alongside the fourth-year students taking the physics part of the integrated Cambridge Natural Science course, commonly referred to as Part III physics. Details of the current Part III physics course can be found on the Department of Physics website.

The MASt in Physics should not be confused with the MASt courses in Mathematics and in Astrophysics, each of which provides an alternative taught master's course with physics components.

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The MPhil is offered by the Department of Physics as a full-time period of research and introduces students to research skills and specialist knowledge. Students are integrated into the research culture of the Department by joining a research group. They are expected to attend the Department’s programme of research seminars and other postgraduate courses but most research training is provided within the group structure and overseen by their supervisor.

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The PhD in Physics is a full-time period of research which introduces or builds upon, research skills and specialist knowledge. Applications for part-time study may also be considered but there are attendance requirements that need to be fulfilled. Students are assigned to a research supervisor, a specialist in part or all of the student's chosen research field, and join a research group which might vary in size between a handful to many tens of individuals. Details of the various research groups can be found on the Research Groups page on the Department of Physics website.

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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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From the Department of Chemistry

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 Materials Science and Metallurgy

The MPhil in Micro and Nanotechnology Enterprise is an exciting opportunity in which world-leading scientists and successful entrepreneurs are brought together to deliver a one-year master’s degree combining an in-depth multidisciplinary scientific programme with a global perspective on the commercial opportunities and business practice necessary for the successful exploitation in the rapidly developing fields of nanotechnology and nanomanufacturing.

The programme is intended for those with a good first degree in the physical sciences and relevant areas of engineering, who wish to develop research skills and commercial awareness of the cutting-edge disciplines of micro- and nanotechnology. The course will provide an unparalleled educational experience for entrepreneurs in these fields.

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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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