"Software is the most prevalent of all the instruments used in modern science" [Goble 2014]. Scientific software is not just widely used [SSI 2014] but also widely developed. Yet much of it is developed by researchers who have little understanding of even the basics of modern software development with the knock-on effects to their productivity, and the reliability, readability and reproducibility of their software [Nature Biotechnology]. Many are long-tail researchers working in small groups - even Big Science operations like the SKA are operationally undertaken by individuals collectively. Technological development in software is more like a cliff-face than a ladder - there are many routes to the top, to a solution. Further, the cliff face is dynamic - constantly and quickly changing as new technologies emerge and decline. Determining which technologies to deploy and how best to deploy them is in itself a specialist domain, with many features of traditional research. Researchers need empowerment and training to give them confidence with the available equipment and the challenges they face. This role, akin to that of an Alpine guide, involves support, guidance, and load carrying. When optimally performed it results in a researcher who knows what challenges they can attack alone, and where they need appropriate support. Guides can help decide whether to exploit well-trodden paths or explore new possibilities as they navigate through this dynamic environment. These guides are highly trained, technology-centric, research-aware individuals who have a curiosity driven nature dedicated to supporting researchers by forging a research software support career. Such Research Software Engineers (RSEs) guide researchers through the technological landscape and form a human interface between scientist and computer. A well-functioning RSE group will not just add to an organisation's effectiveness, it will have a multiplicative effect since it will make every individual researcher more effective. It has the potential to improve the quality of research done across all University departments and faculties. My work plan provides a bottom-up approach to providing RSE services that is distinctive from yet complements the top-down approach provided by the EPRSC-funded Software Sustainability Institute. The outcomes of this fellowship will be: Local and National RSE Capability: A RSE Group at Sheffield as a credible roadmap for others pump-priming a UK national research software capability; and a national Continuing Professional Development programme for RSEs. Scalable software support methods: A scalable approach based on "nudging", to providing research software support for scientific software efficiency, sustainability and reproducibility, with quality-guidelines for research software and for researchers on how best to incorporate research software engineering support within their grant proposals. HPC for long-tail researchers: 'HPC-software ramps' and a pathway for standardised integration of HPC resources into Desktop Applications fit for modern scientific computing; a network of HPC-centric RSEs based around shared resources; and a portfolio of new research software courses developed with partners. Communication and public understanding: A communication campaign to raise the profile of research software exploiting high profile social media and online resources, establishing an informal forum for research software debate. References [Goble 2014] Goble, C. "Better Software, Better Research". IEEE Internet Computing 18(5): 4-8 (2014) [SSI 2014] Hettrick, S. "It's impossible to conduct research without software, say 7 out of 10 UK researchers" http://www.software.ac.uk/blog/2014-12-04-its-impossible-conduct-research-without-software-say-7-out-10-uk-researchers (2014) [Nature 2015] Editorial "Rule rewrite aims to clean up scientific software", Nature Biotechnology 520(7547) April 2015

Many technological advances in modern day life are dependent upon the development of new materials, or better control and understanding of existing materials. Understanding the detailed properties of materials has therefore never been more important. The development of high quality computer simulation techniques has played an increasingly significant role in this endeavour over recent years. The UK has been at the forefront of this new wave, and the UKCP consortium has played an important part, in both developing computer codes and algorithms, and exploiting these new advances to increase our understanding of many industrially relevant materials and processes. The preferred mechanism for providing computational resources on the UK national supercomputer (ARCHER) is via large research consortia, and this proposal funds the UKCP consortium. This is a large and established consortium, containing 22 different nodes and over 160 active researchers. Each node is a different University Department and is represented by one key academic - see the "Linked Proposals" or the Track Record for a complete list of current members of UKCP. This proposal seeks computational support for a large body of research (see "Other Support") with a substantial allocation of ARCHER resources and also the support of a named Research Software Engineer (RSE). The RSE will assist with training and supporting different members of the consortium in using the principle codes used within the consortium (e.g. CASTEP), and also develop some of the new code features required to complete some of these projects. As part of this proposal, the researchers will have to develop new algorithms and also make theoretical improvements that will increase our simulation abilities (either by increasing the accuracy and reliability of calculations, or by enabling us to simulate bigger systems for longer). New algorithms include machine learning to generate new model potentials derived from accurate quantum mechanical calculations for fast calculations of large systems, improved structure optimisation, and uncertainty quantification. New functionality includes new spectroscopies, including magnetic structure, vibrations, neutron scattering and muon decay. Together, these innovations will enable the next generation of simulations and further widen our computational horizons. The research described in this proposal will make significant impacts on many areas of future technology, such as semiconductor nanostructures, protein-drug optimization, ultra-high temperature ceramics, nanoscale devices, hybrid perovskites and solar cells and inorganic nanotubes and metal-air battery anodes. There are also areas of fundamental research, designed to push our understanding of basic properties of matter, such as interfacial water, nanocrystal growth, structure of grain boundaries, pigment-protein complexes, radiation damage in DNA and high-pressure hydrogen phases. The research proposed does not easily fit into any of the traditional categories of 'physics' or 'chemistry' etc. Instead, the UKCP is a multi-disciplinary consortium using a common theoretical foundation to advance many different areas of materials-based science which has the potential for significant impact both in the short and long-term.

In the UK, musculoskeletal disorders (joint and back problems) affect one in five people long term. While joint replacements are successful, they are challenged by demands of an active and younger population presenting with disorders due to trauma, obesity, or other lifestyle choices. One of the causes for joint and back pain is the deterioration of the different soft tissues acting as cushions in the joints. New surgical interventions are being developed to repair or locally replace those soft tissues in order to delay or prevent a total joint replacement. There is no clear indication yet on which patients benefit the most from them. There is an urgent need to define the type of patients for which new and existing interventions are most beneficial. The local anatomy or level of tissue deterioration differs greatly between patients, and there is currently a lack of biomechanical evidence that takes into account these large variations to help matching patients to interventions. To tackle these issues, this Fellowship, MSKDamage, will develop novel testing methods and tools combining laboratory simulation with computer modelling and imaging. MSKDamage methods will be used to predict the variation in the mechanical performance of a series of treatments at various levels of joint deterioration. This will enable the different interventions to be matched to different patient's characteristics. I will focus on three musculoskeletal disorders and associated repairs: 1. Emerging treatments involving the injection of biomaterials in the intervertebral disc: I will produce realistic testing conditions that can be personalised to a specific patient, assessing each patient's chance of success and identifying areas for treatment optimisation. 2. Evaluation of meniscus repairs in the knee and their interaction with cartilage defects: I will provide new information on the type of cartilage defect that reduces the chances of success of a meniscus replacement in the knee. The research will develop guidance on the type of cartilage defects that need repair for a meniscus replacement to be successful. 3. Optimisation of custom wrist repair: I will help optimise patient-specific wrist repairs so that they reduce the damage in tendons and ligaments in the wrist. MSKDamage builds on my strong track-record in the field and network of industry, clinical and academic collaborators, as well as my recent work that demonstrates the specific information which need to be included in models of degraded tissues in the spine and the knee. MSKDamage aims to (1) develop a methodology to test interventions for a specific patient and its specific tissue degradation, (2) carry out a series of case studies which demonstrate the capacity to test a range tissues disorders and repairs. This work is a particularly suitable for a Fellowship, as it will allow me to develop fundamental engineering tools and methods while engaging with end users for significant economic and societal impact. I will also develop as a leader in the field, leading a growing research group and taking actions for the research community, directly related to the research, with advocacy on sharing more research outcomes openly for creation of more impact, and indirectly related to act as an ambassador for public and patient involvement for research related to computer simulations in healthcare.

Soft tissue related diseases (heart, cancer, eyes) are among the leading causes of death worldwide. Despite extensive biomedical research, a major challenge is a lack of mathematical models that predict soft tissue mechanics across subcellular to whole organ scales during disease progression. Given the tremendous scope, the unmet clinical needs, our limited manpower, and the existence of complementary expertise, we seek to forge NEW collaborations with two world-leading research centres: MIT and POLIMI, to embark on two challenging themes that will significantly stretch the initial SofTMech remit: A) Test-based microscale modelling and upscaling, and B) Beyond static hyperelastic material to include viscoelasticity, nonlinear poroelasticity, tissue damage and healing. Our research will lead to a better understanding of how our bodies work, and this knowledge will be applied to help medical researchers and clinicians in developing new therapies to minimise the damage caused by disease progression and implants, and to develop more effective treatments. The added value will be a major leap forward in the UK research. It will enable us to model soft tissue damage and healing in many clinical applications, to study the interaction between tissue and implants, and to ensure model reproducibility through in vitro validations. The two underlying themes will provide the key feedback between tissue and cells and the response of cells to dynamic local environments. For example, advanced continuum mechanics approaches will shed new light on the influence of cell adhesion, angiogenesis and stromal cell-tumour interactions in cancer growth and spread, and on wound healing implant insertion that can be tested with in vitro and in vivo systems. Our theoretical framework will provide insight for the design of new experiments. Our proposal is unique, timely and cost-effectively because advances in micro- and nanotechnology from MIT and POLIMI now enable measurements of sub-cellular, single cell, and cell-ECM dynamics, so that new theories of soft tissue mechanics at the nano- and micro-scales can be tested using in vitro prototypes purposely built for SofTMech. Bridging the gaps between models at different scales is beyond the ability of any single centre. SofTMech-MP will cluster the critical mass to develop novel multiscale models that can be experimentally tested by biological experts within the three world-leading Centres. SofTMech-MP will endeavour to unlock the chain of events leading from mechanical factors at subcellular nanoscales to cell and tissue level biological responses in healthy and pathological states by building a new mathematics capacity. Our novel multiscale modelling will lead to new mathematics including new numerical methods, that will be informed and validated by the design and implementation of experiments at the MIT and POLIMI centres. This will be of enormous benefit in attacking problems involving large deformation poroelasticity, nonlinear viscoelasticity, tissue dissection, stent-related tissue damage, and wound healing development. We will construct and analyse data-based models of cellular and sub-cellular mechanics and other responses to dynamic local anisotropic environments, test hypotheses in mechanistic models, and scale these up to tissue-level models (evolutionary equations) for growth and remodelling that will take into account the dynamic, inhomogeneous, and anisotropic movement of the tissue. Our models will be simulated in the various projects by making use of the scientific computing methodologies, including the new computer-intensive methods for learning the parameters of the differential equations directly from noisy measurements of the system, and new methods for assessing alternative structures of the differential equations, corresponding to alternative hypotheses about the underlying biological mechanisms.

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.