The CDT in Advanced Automotive Propulsion Systems will produce the graduates who will bring together the many technical disciplines and skills needed to allow propulsion systems to transition to a more sustainable future. By creating an environment for our graduates to research new propulsion systems and the wider context within which they sit, we will form the individuals who will lead the scientific, technological, and behavioural changes required to effect the transformation of personal mobility. The CDT will become an internationally leading centre for interdisciplinary doctoral training in this critical field for UK industrial strategy. We will train a cohort of 84 high quality research leaders, adding value to academia and the UK automotive industry. There are three key aspects to the success of the CDT - First, a diverse range of graduates will be recruited from across the range of first degrees. Graduates in engineering (mechanical, electrical, chemical), sciences (physics, chemistry, mathematics, biology), management and social sciences will be recruited and introduced to the automotive propulsion sector. The resulting skills mix will allow transformational research to be conducted. Second, the training given to this cohort, re-enforced by a strong group working ethos, will prepare the graduates to make an effective contribution to the industry. This will require training in the current and future methods (technical and commercial) used by the industry. We also need the graduates to have highly developed interpersonal skills and to be experienced in effective group working. Understanding how people and companies work is just as important as an understanding the technology. On the technology side, a broad system level understanding of the technology landscape and the relationship between the big picture and the graduate's own expertise is essential. We have designed a programme that enriches the student's knowledge and experience in these key areas. Third, underpinning all of these attributes will be the graduate's research skills, acquired through the undertaking of an intensive research project within the new £60 million Institute for Advanced Automotive Propulsion Systems (IAAPS), designed from the outset to provide a rich collaborative environment and add value to the UK economy. IAAPS will be equipped with world leading experimental facilities designed for future powertrain systems and provides dedicated space for industry and academia to collaborate to deliver research valued at over £100 million during the lifetime of the CDT. The cohort will contribute to and benefit from this knowledge development, providing opportunities to conduct research at a whole system level. This will address one of the most pressing challenges of our age - the struggle to provide truly sustainable, affordable, connected, zero emissions transport needed by both industrialised and emerging economies. To enable these benefits we request funding for 40 studentships and the infrastructure to provide a world class training environment. The university will enhance this through the funding of an additional 20 studentships and access to research facilities, together valued at £5 million. Cash and in-kind contributions from industrial partners valued at a total of £4.5 million will enhance the student experience, providing 9 fully funded PhD places and 30 half funded places. The research undertaken by the students will be co-created and supervised by our industrial partners. The people and research outputs that from the CDT will be adopted directly by these industrial partners to generate lasting real world impact.

Data science and artificial intelligence will transform the way in which we live and work, creating new opportunities and challenges to which we must respond. Some of the greatest opportunities lie in the field of human health, where data science can help us to predict and diagnose disease, determine the effectiveness of existing treatments, and improve the quality and affordability of care. The Oxford EPSRC CDT in Health Data Science will provide training in: - core data science principles and techniques, drawing upon expertise in computer science, statistics, and engineering - the interpretation and analysis of different kinds of health data, drawing upon expertise in genomics, imaging, and sensors - the methodology and practice of health data research, drawing upon expertise in population health, epidemiology, and research ethics The training will be provided by academics from five university departments, working together to provide a coordinated programme of collaborative learning, practical experience, and research supervision. The CDT will be based in the Oxford Big Data Institute (BDI), a hub for multi-disciplinary research at the heart of the University's medical campus. A large area on the lower ground floor of the BDI building will be allocated to the CDT. This area will be refurbished to provide study space for the students, and dedicated teaching space for classes, workshops, group exercises, and presentations. Oxford University Hospitals NHS Foundation Trust (OUH), one of the largest teaching hospitals in the UK, will provide access to real-world clinical and laboratory data for training and research purposes. OUH will provide also access to expertise in clinical informatics and data governance, from a practical NHS perspective. This will help students to develop a deep understanding of health data and the mechanisms of healthcare delivery. Industrial partners - healthcare technology and pharmaceutical companies - will contribute to the training in other ways: helping to develop research proposals; participating in data challenges and workshops; and offering placements and internships. This will help students to develop a deep understanding of how scientific research can be translated into business innovation and value. The Ethox Centre, also based within the BDI building, will provide training in research ethics at every stage of the programme, and the EPSRC ORBIT team will provide training in responsible research and innovation. Ethics and research responsibility are central to health data science, and the CDT will aim to play a leading role in developing and demonstrating ethical, responsible research practices. The CDT will work closely with national initiatives in data science and health data research, including the ATI and HDR UK. Through these initiatives, students will be able to interact with researchers from a wide network of collaborating organisations, including students from other CDTs. There will also be opportunities for student exchanges with international partners, including the Berlin Big Data Centre. Students graduating from the CDT will be able to understand and explore complex health datasets, helping others to ask questions of the data, and to interpret the results. They will be able to develop the new algorithms, methods, and tools that are required. They will be able to create explanatory and predictive models for disease, helping to inform treatment decisions and health policy. The emphasis upon 'team science' and multi-disciplinary working will help to ensure that our students have a lasting, positive impact beyond their own work, delivering value for the organisations that they join and for the whole health data science community.

We are witnessing huge global shifts towards cleaner growth and more resource efficient economies. The drive to lower carbon emissions is resulting in dramatic changes in how we travel and the ways we generate and use energy worldwide. Electrical machines are at the heart of the accelerating trends in the electrification of transport and the increased use of renewable energy such as offshore wind. To address the pressing drivers for clean growth and meet the increasing demands of new applications, new electrical machines with improved performance - higher power density, lower weight, improved reliability - are being designed by researchers and industry. However, there are significant manufacturing challenges to be overcome if UK industry is going to be able to manufacture these new machines with the appropriate cost, flexibility and quality. The Hub's vision is to put UK manufacturing at the forefront of the electrification revolution. The Hub will address key manufacturing challenges in the production of high integrity and high value electrical machines for the aerospace, energy, high value automotive and premium consumer sectors. The Hub will work in partnership with industry to address some common and fundamental barriers limiting manufacturing capability and capacity: the need for in-process support to manual operations in electrical machine manufacture - e.g. coil winding, insertions, electrical connections and wiring - to improve productivity and provide quality assurance; the sensitivity of high value and high integrity machines to small changes in tolerance and the requirement for high precision in manufacturing for safety critical applications; the increasing drive to low batch size, flexibility and customisation; and the need to train the next generation of manufacturing scientists and engineers. The Hub's research programme will explore new and emerging manufacturing processes, new materials for enhanced functionality and/or light-weighting, new approaches for process modelling and simulation, and the application of digital approaches with new sensors and Industrial Internet of Things (IoT) technologies.

The Centre for Doctoral Training MAC-MIGS will provide advanced training in the formulation, analysis, and implementation of state-of-the-art mathematical and computational models. The vision for the training offered is that effective modern modelling must integrate data with laws framed in explicit, rigorous mathematical terms. The CDT will offer 76 PhD students an intensive 4-year training and research programme that equips them with the skills needed to tackle the challenges of data-intensive modelling. The new generation of successful modelling experts will be able to develop and analyse mathematical models, translate them into efficient computer codes that make best use of available data, interpret the results, and communicate throughout the process with users in industry, commerce and government. Mathematical and computational models are at the heart of 21st-century technology: they underpin science, medicine and, increasingly, social sciences, and impact many sectors of the economy including high-value manufacturing, healthcare, energy, physical infrastructure and national planning. When combined with the enormous computing power and volume of data now available, these models provide unmatched predictive tools which capture systematically the experimental and observational evidence available. Because they are based on sound deductive principles, they are also the only effective tool in many problems where data is either sparse or, as is often the case, acquired in conditions that differ from the relevant real-world scenarios. Developing and exploiting these models requires a broad range of skills - from abstract mathematics to computing and data science - combined with expertise in application areas. MAC-MIGS will equip its students with these skills through a broad programme that cuts across disciplinary boundaries to include mathematical analysis - pure, applied, numerical and stochastic - data-science and statistics techniques and the domain-specific advanced knowledge necessary for cutting-edge applications. MAC-MIGS students will join the broader Maxwell Institute Graduate School in its brand-new base located in central Edinburgh. They will benefit from (i) dedicated academic training in subjects that include mathematical analysis, computational mathematics, multi-scale modelling, model reduction, Bayesian inference, uncertainty quantification, inverse problems and data assimilation, and machine learning; (ii) extensive experience of collaborative and interdisciplinary work through projects, modelling camps, industrial sandpits and internships; (iii) outstanding early-career training, with a strong focus on entrepreneurship; and (iv) a dynamic and forward-looking community of mathematicians and scientists, sharing strong values of collaboration, respect, and social and scientific responsibility. The students will integrate a vibrant research environment, closely interacting with some 80 MAC-MIGS academics comprised of mathematicians from the universities of Edinburgh and Heriot-Watt as well as computer scientists, engineers, physicists and chemists providing their own disciplinary expertise. Students will benefit from MAC-MIGS's diverse network of more than 30 industrial and agency partners spanning a broad spectrum of application areas: energy, engineering design, finance, computer technology, healthcare and the environment. These partners will provide internships, development programmes and research projects, and help maximise the impact of our students' work. Our network of academic partners representing ten leading institutions in the US and Europe, will further provide opportunities for collaborations and research visits.