Open science is perhaps best embodied by the FAIR principles for software and data: that they should be Findable, Accessible, Interoperable, and Reusable. When researchers make their code and data available for others to use, it becomes easier for others to verify results, as well as easier for others to build on and use to spur new research of their own. Alongside the FAIR principles is the idea of "sustainable" software, which is software that can continue to be used after its original intended purpose, remaining reliable and reproducible. Sustainable software is important for high quality research. The goal of this Fellowship is to help researchers in plasma science overcome barriers to implementing these principles and ideas in their work, and bring about a cultural change to make sharing FAIR software and data the norm. I will do this by establishing a national network of research software engineers (RSEs) who will undertake efficient, wide-ranging improvements across the plasma science software ecosystem. The objective is not to make a single code massively better; it is to create and maintain an environment and philosophy that will benefit all plasma codes used in the UK -- "a rising tide lifts all boats". In order to reach as much of the community as possible, this national network will focus on short usability and sustainability projects, along with training tailored to individual researchers and groups. This will be paired with code review, where an RSE will go through a piece of software with researchers and discuss its aims and implementation. Code review is commonplace in industry, but rarer in academia. Together, the use of code review and short projects will give the network a good idea of what software is needed and used by the community, targeting projects where they are most needed and encouraging reuse of software between groups. As well as improving software directly, I will also work on the data front. To do this, I will develop tools to help overcome the friction and effort needed for researchers to adopt FAIR data practices. These tools will add metadata output to software, capturing important information like what version of what code created the output. This metadata can then be used to automate uploading the output to a database. I will work with the plasma science and data communities to develop what this metadata will look like, while the national network will implement these tools across the plasma science software ecosystem.

The achievements of modern research and their rapid progress from theory to application are increasingly underpinned by computation. Computational approaches are often hailed as a new third pillar of science - in addition to empirical and theoretical work. While its breadth makes computation almost as ubiquitous as mathematics as a key tool in science and engineering, it is a much younger discipline and stands to benefit enormously from building increased capacity and increased efforts towards integration, standardization, and professionalism. The development of new ideas and techniques in computing is extremely rapid, the progress enabled by these breakthroughs is enormous, and their impact on society is substantial: modern technologies ranging from the Airbus 380, MRI scans and smartphone CPUs could not have been developed without computer simulation; progress on major scientific questions from climate change to astronomy are driven by the results from computational models; major investment decisions are underwritten by computational modelling. Furthermore, simulation modelling is emerging as a key tool within domains experiencing a data revolution such as biomedicine and finance. This progress has been enabled through the rapid increase of computational power, and was based in the past on an increased rate at which computing instructions in the processor can be carried out. However, this clock rate cannot be increased much further and in recent computational architectures (such as GPU, Intel Phi) additional computational power is now provided through having (of the order of) hundreds of computational cores in the same unit. This opens up potential for new order of magnitude performance improvements but requires additional specialist training in parallel programming and computational methods to be able to tap into and exploit this opportunity. Computational advances are enabled by new hardware, and innovations in algorithms, numerical methods and simulation techniques, and application of best practice in scientific computational modelling. The most effective progress and highest impact can be obtained by combining, linking and simultaneously exploiting step changes in hardware, software, methods and skills. However, good computational science training is scarce, especially at post-graduate level. The Centre for Doctoral Training in Next Generation Computational Modelling will develop 55+ graduate students to address this skills gap. Trained as future leaders in Computational Modelling, they will form the core of a community of computational modellers crossing disciplinary boundaries, constantly working to transfer the latest computational advances to related fields. By tackling cutting-edge research from fields such as Computational Engineering, Advanced Materials, Autonomous Systems and Health, whilst communicating their advances and working together with a world-leading group of academic and industrial computational modellers, the students will be perfectly equipped to drive advanced computing over the coming decades.

Advances in High Performance Computing (HPC) and scientific software development will have increasingly significant societal impact through the computational design of new products, medicines, materials and industrial processes. However, the complexity of modern HPC hardware means that scientific software development now requires teams of scientists and programmers to work together, with different and non-overlapping skill-sets required from each member of the group. This complexity can lead to software development projects stalling. Investments in software development are in danger of being lost, either because key members of a team move on, or because a lack of planning or engagement means that a sustainable user and developer community has failed to gel around a particular code. Research Software Engineers (RSEs) can solve this problem. RSEs have the skills and training necessary to support software development projects as they move through different stages of the academic software lifecycle. Academic software evolves along this lifecycle, from being a code used by an initial team of researchers, through to a large multi-site community code used by academics and industrialists from across the UK and around the World. RSEs provide the training and support needed to help academic software developers structure their projects to support the sustainable growth of their user and developer communities. RSEs are also highly skilled programmers who can train software developers in advanced HPC techniques, and who can support developers in the implementation, optimisation and testing of complex and intricate code. Together with academic software developers, RSEs can support UK investment in HPC, and ensure that the potential of computational science and engineering to revolutionise the design of future products and industrial processes is realised. This project aims to develop sustainable RSE career pathways and funding at Bristol. This will support the growth of a sustainable team of RSEs at the University. Software development projects that will be supported include; the building of code to interface real biological cells with virtual simulated cells, so to support the rapid design of new biomanufacturing control processes; the development of code to more quickly model the behaviour of electrons in novel materials, to support the design of new fuel cells and batteries; code to improve our understanding of glass-like matter, so to help design new materials with exciting new properties; software to support modelling of the quantum interaction between laser light and microscopic nanoparticles, to support the design of optical tweezers and new optically driven nanomachines; and code to design new medicinal drugs and to understand why existing treatments are no longer working, thereby supporting the development of 21st century medicine. Finally, this project aims to create a coherent set of teaching materials in programming and research software engineering. These, together with the development of software to support science and programming lessons held in an interactive 3D planetarium, will help inspire and educate the next generation of scientists and RSEs. These materials will showcase how maths, physics, computing and chemistry can be used in the "real world" to create the high-tech tools and industries of the future.

The field of Atomic, Molecular and Optical (AMO) physics holds the promise of unlocking some of the deepest secrets of the universe. It straddles the gap between the mysterious, quantum world, and the world of chemistry which determines much of our lived experience. While several software tools exist to probe particular niches, there is only a very limited and uncoordinated effort to consolidate these disparate strands of development. In this project I will bring together my expertise in this scientific area with an ever-growing network of researchers therein to assemble a useable, sustainable and impactful toolset for researchers. The main outcome of the project will be a computational package (PARAMOR) which is accessible to a large number of non-expert users, which may be developed sustainably by the community, and which will consolidate previously disparate development strands into a concerted effort. The package will run the most sophisticated high-performance AMO physics computer codes under the surface and provide a clean and easy-to-use interface to the user for designing and running simulations, and for processing and rendering their outputs. The main impact will be to inaugurate a vibrant, global user-community of AMO physics codes that reverses the 'normal' tendency for scientific codes to stagnate, or become increasingly specialised, and create a truly sustainable and impactful resource for physics research generally. The current status-quo in AMO computational physics is for very gifted lone developers or small teams to build immensely complex and very capable software, which is practically inaccessible to outsiders. This project will thus act to bridge the gap and allow the potential impact of these separate efforts to be realised, as well as bringing the benefits of modern software development techniques into the AMO physics world.

In the last decade, the role of software engineering has changed rapidly and radically. Globalisation and mobility of people and services, pervasive computing, and ubiquitous connectivity through the Internet have disrupted traditional software engineering boundaries and practices. People and services are no longer bound by physical locations. Computational devices are no longer bound to the devices that host them. Communication, in its broadest sense, is no longer bounded in time or place. The Software Engineering & Design (SEAD) group at the Open University (OU) is leading software engineering research in this new reality that requires a paradigm shift in the way software is developed and used. This platform grant will grow and sustain strategic, multi-disciplinary, crosscutting research activities that underpin the advances in software engineering required to build the pervasive and ubiquitous computing systems that will be tightly woven into the fabric of a complex and changing socio-technical world. In addition to sustaining and growing the SEAD group at the OU and supporting its continued collaboration with the Social Psychology research group at the University of Exeter, the SAUSE platform will also enable the group to have lasting impact across several application domains such as healthcare, aviation, policing, and sustainability. The grant will allow the team to enhance the existing partner networks in these areas and to develop impact pathways for their research, going beyond the scope and lifetime of individual research projects.