In our work in the current edition of the CMIH we have built up a strong pool of researchers and collaborations across the board from mathematics, statistics, to engineering, medical physics and clinicians. Our work has also confirmed that imaging data is a very important diagnostic biomarker, but also that non-imaging data in the form of health records, memory tests and genomics are precious predictive resources and that when combined in appropriate ways should be the source for AI-based healthcare of the future. Following this philosophy, the new CMIH brings together researchers from mathematics, statistics, computer science and medicine, with clinicians and relevant industrial stakeholder to develop rigorous and clinically practical algorithms for analysing healthcare data in an integrated fashion for personalised diagnosis and treatment, as well as target identification and validation on a population level. We will focus on three medical streams: Cancer, Cardiovascular disease and Dementia, which remain the top 3 causes of death and disability in the UK. Whilst applied mathematics and mathematical statistics are still commonly regarded as separate disciplines there is an increasing understanding that a combined approach, by removing historic disciplinary boundaries, is the only way forward. This is especially the case when addressing methodological challenges in data science using multi-modal data streams, such as the research we will undertake at the Hub. This holistic approach will support the Hub aims to bring AI for healthcare decision making to the clinical end users.

The Industrial Doctorate Centre in Molecular Modelling and Materials Science (M3S) at University College London (UCL) trains researchers in materials science and simulation of industrially important applications. As structural and physico-chemical processes at the molecular level largely determine the macroscopic properties of any material, quantitative research into this nano-scale behaviour is crucially important to the design and engineering of complex functional materials. The M3S IDC is a highly multi-disciplinary 4-year EngD programme, which works in partnership with a large base of industrial sponsors on a variety of projects ranging from catalysis to thin film technology, electronics, software engineering and bio-physics research. The four main research themes within the Centre are 1) Energy Materials and Catalysis; 2) Information Technology and Software Engineering; 3) Nano-engineering for Smart Materials; and 4) Pharmaceuticals and Bio-medical Engineering. These areas of research align perfectly with EPSRC's mission programmes: Energy, the Digital Economy, and Nanoscience through Engineering to Application. In addition, per definition an industrial doctorate centre is important to EPSRC's priority areas of Securing the Future Supply of People and Towards Better Exploitation. Students at the M3S IDC follow a tailor-made taught programme of specialist technical courses, as well as professionally accredited project management courses and transferable skills training, which ensures that whatever their first degree, on completion all students will have obtained thorough technical and managerial schooling as well as a doctoral research degree. The EngD research is industry-led and of comparable high quality and innovation as the more established PhD research degree. However, as the EngD students spend approximately 70% of their time on site with the industrial sponsor, they also gain first hand experience of the demanding research environment of a successful, competitive industry. Industrial partners who have taken up the opportunity during the first phase of the EngD programme to add an EngD researcher to their R&D teams include Johnson Matthey, Pilkington Glass, Exxon Mobil, Silicon Graphics, Accelrys and STS, while new companies are added to the pool of sponsors each year. Materials research in UCL is particularly well developed, with a thriving Centre for Materials Research and a newly established Materials Chemistry Centre. In addition, the Bloomsbury campus has perhaps the largest concentration of computational materials scientists in the UK, if not the world. Although affiliated to different UCL departments, all computational materials researchers are members of the UCL Materials Simulation Laboratory, which is active in advancing the development of common computational methodologies and encouraging collaborative research between the members. As such, UCL has a large team of well over a hundred research-active academic staff available to supervise research projects, ensuring that all industrial partners will be able to team up with an academic in a relevant research field to form the supervisory team to work with the EngD student. The success of the existing M3S Industrial Doctorate Centre and the obvious potential to widen its research remit and industrial partnerships into new, topical materials science areas, which are at the heart of EPSRC's strategic funding priorities for the near future, has led to this proposal for the funding of 5 annual cohorts of ten EngD students in the new phase of the Centre from 2009.

The Centre for Doctoral Training in "Molecular Modelling and Materials Science" (M3S CDT) at University College London (UCL) will deliver to its students a comprehensive and integrated training programme in computational and experimental materials science to produce skilled researchers with experience and appreciation of industrially important applications. As structural and physico-chemical processes at the molecular level largely determine the macroscopic properties of any material, quantitative research into this nano-scale behaviour is crucially important to the design and engineering of complex functional materials. The M3S CDT offers a highly multi-disciplinary 4-year doctoral programme, which works in partnership with a large base of industrial and external sponsors on a variety of projects. The four main research themes within the Centre are 1) Energy Materials; 2) Catalysis; 3) Healthcare Materials; and 4) 'Smart' Nano-Materials, which will be underpinned by an extensive training and research programme in (i) Software Development together with the Hartree Centre, Daresbury, and (ii) Materials Characterisation techniques, employing Central Facilities in partnership with ISIS and Diamond. Students at the M3S CDT follow a tailor-made taught programme of specialist technical courses, professionally accredited project management courses and generic skills training, which ensures that whatever their first degree, on completion all students will have obtained thorough technical schooling, training in innovation and entrepreneurship and managerial and transferable skills, as well as a challenging doctoral research degree. Spending >50% of their time on site with external sponsors, the students gain first-hand experience of the demanding research environment of a competitive industry or (inter)national lab. The global and national importance of an integrated computational and experimental approach to the Materials Sciences, as promoted by our Centre, has been highlighted in a number of policy documents, including the US Materials Genome Initiative and European Science Foundation's Materials Science and Engineering Expert Committee position paper on Computational Techniques, Methods and Materials Design. Materials Science research in the UK plays a key role within all of the 8 Future Technologies, identified by Science Minister David Willetts to help the UK acquire long-term sustainable economic growth. Materials research in UCL is particularly well developed, with a thriving Centre for Materials Research, a Materials Chemistry Centre and a new Centre for Materials Discovery (2013) with a remit to build close research links with the Catalysis Technology Hub at the Harwell Research Complex and the prestigious Francis Crick Institute for biomedical research (opening in 2015). The M3S will work closely with these centres and its academic and industrial supervisors are already heavily involved with and/or located at the Harwell Research Complex, whereas a number of recent joint appointments with the Francis Crick Institute will boost the M3S's already strong link with biomedicine. Moreover, UCL has perhaps the largest concentration of computational materials scientists in the UK, if not the world, who interact through the London-wide Thomas Young Centre for the Theory and Simulation of Materials. As such, UCL has a large team of well over 100 research-active academic staff available to supervise research projects, ensuring that all external partners can team up with an academic in a relevant research field to form a supervisory team to work with the Centre students. The success of the existing M3S CDT and the obvious potential to widen its research remit and industrial partnerships into topical new materials science areas, which lie at the heart of EPSRC's strategic funding priorities and address national skills gaps, has led to this proposal for the funding of 5 annual student cohorts in the new phase of the Centre.

Traditional engineering ignores complex interactions across several space-time scales, which does not fit the context of modelling of biological systems where scales overlap and the inherent complexity of multi-scale interaction cannot be avoided. For this reason, in the previously funded MultiSim project, we established a computational platform for the investigation of musculoskeletal disorders, which we successfully applied to the prediction of the risk of fracture in osteoporotic and osteopenic women, and to the pre-clinical investigation of bone remodelling in animal models to assess the effect of new treatments. Full exploitation of this platform, however, is limited by the fact that most of the MultiSim activities evolved around skeletal health only. MultiSim2 will allow us to expand the focus of our Centre to include an equivalently robust and detailed modelling of the skeletal muscles to predict the effects of pathologies such as sarcopenia or neurodegenerative diseases. To do so, we will develop new approaches for better imaging, characterisation and modelling of the muscles and of their interaction with the skeletal system. In our murine work, we will focus on developing noninvasive longitudinal imaging techniques and computational models to support the reduction and partial replacement of the use of mice in musculoskeletal research. We will measure longitudinal changes in muscle properties by using a micro-magnetic resonance imaging (microMRI) system and advanced image processing to predict tissue changes over time. These measurements will be integrated to a framework of available tools to obtain bone properties at high resolution with in vivo micro-Computed Tomography (microCT) and to co-register all the acquired data in space and time. We will use our human models to predict physiological and pathological changes of muscle volumes and masses, variations in muscle fibres, tendon geometric and elastic properties and changes associated with degeneration in the neuromotor control. The comprehensive assessment of changes in different musculoskeletal tissues (bone, muscles, tendons) over time in both patients and animals will allow us to create a combined experimental and computational framework to better understand and model the effect of diseases and to optimise future treatments.

The aim of this research is to enable future energy materials by improving their performance. This will be done by establishing a novel methodology combining advanced microscopy and modelling to understand how the atomistic behaviour controls their macroscopic properties. The properties and behaviour of materials are controlled by what is happening at the atomic scale. Understanding this relationship can lead to the optimisation of existing materials and the design of new ones. However, it can be hard to know enough about the structure and bonding at the atomistic level (i.e. the local chemistry) to accurately predict the properties of a material. Recent advances in electron microscopy combined with theoretical developments carried out as part of this research mean that we can now take a step forward in this field and start solving problems involving important functional materials. Knowing how the local chemistry is related to the macroscopic properties is a crucial part of designing and optimising materials for energy applications. This research focuses on three energy materials systems which have the potential to make an enormous impact on the economy and environment. The first of these involves development of a new transparent conducing oxide (TCO). TCOs are used in flat panel displays, such as smart phones and televisions, and solar cells. The most commonly used TCO contains indium, which has a high supply risk, and the manufacturing process to make it is very energy intensive. Development of a TCO which does not contain indium and is produced by low energy methods is crucial to the sustainability of a variety of technological applications. This work aims to improve the performance of a new TCO material by relating the electrical and optical properties to the local chemistry. The second material being investigated in this research is catalyst particles for use in fuel cells. Fuel cells are a viable way of making road vehicles which emit fewer greenhouse gases. A reduction in the greenhouse gas emissions (GGEs) from transport is an important part of the UK's plan to reduce GGEs by 2050. The catalyst studied here forms part of the fuel cell which needs optimising before fuel cells can become a mainstream energy technology. The last material system that this work will investigate is metals containing hydrogen. Metal and metal alloy components used in many engineering applications suffer from devastating failure as a result of hydrogen embrittlement. These include materials used in oil pipelines, nuclear reactors and the components that would be used to make hydrogen fuel a reality. Exactly how this happens is not known but being able to understand where the hydrogen is in the material is a crucial step towards not only understanding the mechanism but guarding against it.