The Oxford Masters in Mathematical Sciences (OMMS) provides a broad and flexible training in the mathematical sciences and offers students with a keen interest in the mathematical sciences the opportunity to work with an international group of peers, including other mathematical leaders of the future. The course is taught jointly by the Mathematical Institute and the Department of Statistics, and runs from the beginning of October through to the end of June. OMMS students can tailor the programme to their individual interests and requirements by choosing from many options in mathematics and statistics, from number theory, geometry and algebra to genetics and mathematical physiology; from probability and mathematical geoscience to data mining and machine learning. The compulsory dissertation provides an opportunity to develop research techniques as well as presentation and scientific communication skills.

This course is supported by XTX Markets.

The MSc in Mathematical and Theoretical Physics is a high-level postgraduate course that takes students from a standard undergraduate degree in Mathematics or Physics to the point where they can do original research. It is a joint course between the Mathematical Institute and the Theoretical Physics department at Oxford, combining topics from both disciplines specially blended together for a truly interdisciplinary programme. The course runs from the beginning of October through to the end of June, and the four main areas covered by the course are: Quantum Field Theory, Particle Physics and String Theory; Theoretical Condensed Matter Physics; Theoretical Astrophysics, Plasma Physics and Physics of Continuous Media; and Mathematical Foundations of Theoretical Physics. Students have great flexibility and can chose one of these areas, or any combination of them.

This course is supported by XTX Markets.

Oxford University’s MSc course in Mathematics and Foundations of Computer Science is a full-time programme that runs from early October through to the following September. It is aimed at students seeking a rigorous and intellectually stimulating experience in the realms of mathematics and computer science. The course is well-suited for individuals who possess a strong foundation in both subjects and have a genuine passion for exploring their interconnections. Prospective students should have a keen interest in abstract reasoning, problem-solving, and a desire to delve into the theoretical underpinnings of computer science. This program attracts students who aspire to deepen their understanding of advanced mathematical concepts and their applications in the field of computer science. It is ideal for those with aspirations in academia, research, or pursuing careers in industries where technical skills in mathematics and computer science are highly valued. The dissertation research projects allow students to pursue a novel research project on a topic that they agree on with an academic supervisor.

This course is supported by XTX Markets.

Oxford University’s MSc In Advanced Computer Science is a full-time programme that runs from early October through to the following September. The MSc in Advanced Computer Science at Oxford has been designed to teach a range of advanced topics to graduates of computer science and other mathematical disciplines, and is designed to combine theory and practice. Entrants to the course will come from either a computer science or mathematical background. You may be a recent graduate in computer science and will supplement your knowledge with the kind of sound mathematical basis which is not always found in undergraduate courses. If you are a graduate in mathematics you will apply your training in the context of a rigorous application of the fundamental techniques of computer science. The course culminates in an agreed project where students can pursue a particular academic interest.

This course is supported by XTX Markets and Google DeepMind.

The MSc in Mathematics and Foundations of Computer Science, run jointly by the Mathematical Institute and the Department of Computer Science is a full time course which focuses on the interface between pure mathematics and theoretical computer science. The mathematical side concentrates on areas where computers are used, or which are relevant to computer science, namely algebra, general topology, number theory, combinatorics and logic. Examples from the computing side include computational complexity, concurrency, and quantum computing. Students take a minimum of five options and write a dissertation. Apart from the dissertation about 75% is taught content and 25% is self-directed learning. The course is suitable for those who wish to pursue research in pure mathematics (especially algebra, number theory, combinatorics, general topology and their computational aspects), mathematical logic, or theoretical computer science. It is also suitable for students wishing to enter industry with an understanding of mathematical and logical design and concurrency.

This course is supported by XTX Markets and Google DeepMind.

The MSc in Statistical Science is a twelve-month, full-time taught master’s with a particular focus on modern computationally-intensive theory and methods and will aim to train you to solve real-world statistical problems. When completing the course, you should be able to choose an appropriate statistical method to solve a given problem of data analysis, implement the analysis on a computer and communicate your results clearly and succinctly. The MSc offers a broad high-level training in applied and computational statistics, statistical machine learning, and the fundamental principles of statistical inference. Training is delivered through mathematically demanding lectures and problems classes, hands-on practical sessions in the computer laboratory, report writing and dissertation supervision. You will have around three months to work on your dissertation with guidance from your supervisor, offering you a substantial opportunity for self-directed study and research. 

This course is supported by Google DeepMind.

A DPhil is Oxford’s name for a PhD – a higher research degree which allows you to make an original contribution to mathematics in the form of a thesis. A DPhil takes at least three years to complete, and around two thirds of our postgraduate leavers go on into academia (according to the latest destination data). During your DPhil, you will be supervised by at least one academic, although some students will have more than one supervisor (particularly if they are working across disciplines). You will begin to do research straight away and there is no prescribed taught component. However, you are very welcome to attend seminars and you can choose from a wide variety of taught courses and skills training to enhance your broader mathematical knowledge and develop your career. There may also be journal clubs or seminar series specific to your area of study. If you enjoy doing mathematics, and would like to be part of a lively and world-class research institute, then you should take a look at the research groups to see if they align with your own interests. 

Find out more here.

This course is supported by XTX Markets.

The Centre for Doctoral Training (CDT) in Fundamentals of AI will undertake foundational research in the underpinning theory and method development of Artificial Intelligence and machine learning that have the potential to have a transformative impact across a range of humane themes associated with the Ellison Institute of Technology (EIT).

The course will provide you with training in both cutting-edge AI research methodologies and the development of business and transferable skills. You will undertake a significant, challenging and original research project, leading to the award of a DPhil. Key topics and themes will focus on fundamentals of artificial intelligence, computational statistics, and machine learning, reflecting the breadth and depth of the research experience of the supervisory pool.

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This course is supported by XTX Markets.

The Autonomous Intelligent Machines and Systems (AIMS) Centre for Doctoral Training (CDT) provides graduates with the opportunity to develop in-depth knowledge, understanding and expertise in autonomous intelligent systems. 

The programme provides a comprehensive, state-of-the-art view of autonomous intelligent systems, combining theoretical foundations, systems research, academic training and industry-initiated projects and thus mixing both practical and theoretical aspects of intelligent machines and systems.

Find out more here.

This course is supported by XTX Markets.

The DPhil in Computer Science is an advanced research degree, awarded for a significant (new) contribution to the existing body of knowledge in the field of computer science. The degree will introduce you to cutting edge research, while you study in a beautiful, historic setting that is both student- and family-friendly.

You will work with world-class experts in their field. Supervision is available in areas corresponding to the department’s research themes. Cross-disciplinary work corresponding to more than one theme, or involving researchers from other departments or from industry, is also possible.

The course combines individual supervision with a selection of lecture courses, transferable skills training and opportunities to participate in cutting-edge research activities. During your study at Oxford, the department hopes to share with you some of the excitement about the topics the department investigates, and of the understanding the department has gained from research into basic theory and by industrial collaboration.

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This course is supported by XTX Markets.

The EPSRC CDT in Fusion Power empowers students to become exceptional fusion scientists and engineers through world-class training and a thriving collaborative community. We support PhD students from diverse backgrounds in developing their expertise and research skills. Our goal is to enhance students’ knowledge and skills within the fusion power sector, enabling them to evaluate complex problems, propose innovative solutions, and navigate the demanding nature of the  evolving landscape of fusion power.

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This course is supported by the UK Atomic Energy Authority.