It is generally accepted now that many real-world problems are best addressed by a number of disciplines working together rather than by individual disciplines alone. In the UK, research councils promote interdisciplinary research activity and universities in turn encourage academics to collaborate with colleagues in other disciplines. It is not always easy, however, for researchers in different areas to cooperate, because each discipline has methods of working, expectations, value systems and ways of talking and writing that are special to that discipline and not easily shared. We believe that it is important for institutions, research councils and researchers to have a fuller understanding of what the distinctive features of discourse practices in interdisciplinary research are and of how they differ from discourse practices in conventional disciplines. As a step toward this goal we propose investigating the discourse of a successful journal in an interdisciplinary field: Environmental Change. We will study the extent to which this field operates as a unified whole, the extent to which journal authors in the field broaden their messages to a multidisciplinary audience, and the extent to which each discipline in the field maintains a discrete identity. In order to investigate the field we will analyse the journal 'Global Environmental Change'. We will include in our study every article published in the journal since its inception in 1990. The primary methodology we use is Corpus Linguistics, that is, using specialised software to analyse large quantities of written text. Many studies of individual disciplines, using corpus techniques, already exist, but these techniques have not yet been applied to an interdisciplinary field. We will use an approach to the description of the linguistic features of texts that will make it possible for us to cluster texts according to degrees of correlation in their linguistic profiles; this approach, developed by Douglas Biber, is called 'multidimensional analysis'. In addition, we will investigate the recurrent phraseologies of texts in this field and then cluster texts with similar phraseological profiles. Using both multidimensional and phraseological clusters, we will see whether the texts cluster following discipline boundaries. This is an innovative approach to corpus-based investigations of research discourse: instead of placing the texts into categories according to external criteria (for example, according to 'discipline'), we will group texts by text-internal features. We will also look at the citation practices (do authors tend to cite within their discipline?) and how writers and readers are represented in the texts (do writers address their readers as experts in their discipline, for example?). We will compare the results of our investigation of the discourse of interdisciplinary research in that journal by comparing it to samples of texts taken from other journals, five representing other interdisciplinary fields and five representing specific disciplines. This will allow us to determine whether interdisciplinary research discourse is distinct in its features, and also to to see how much variation in discourse practices there may be between interdisciplinary fields and within disciplines. We will look at this across time, to see whether discourse practices change as a field becomes more established and as an interdisciplinary community develops. To complement our analyses of texts, we will also conduct surveys and interviews of people involved in the journal publication process: editors, reviewers and authors. The data can help us to explain some of the phenomena that we observe in the texts; the influence of editorial policies, for example, or the ways that authors from different disciplines collaborate to write texts. The work will support the research infrastructure in the UK by increasing our understanding of interdisciplinary research discourse.

Too few women researchers are leading spinout companies. There has not been enough attention focused on the progression of women researchers at all career stages on the entrepreneurial pathway from research to spinout leadership. Whilst challenges relating to women's research career progression are well understood, the STEM community and the Higher Education (HE) sector as a whole are not as well informed about women entrepreneurial career progression pathways to spinout. Research shows that founders and co-founders of university spinout companies are predominantly men. For example, the Enterprise Research Centre (2014) survey of a sample of 350 active UK spinouts found that women were the main founders in only 8.3% of cases. The disproportionately low numbers of women founders are not limited to UK spinouts. Research carried out by Elsevier (2017) comparing the United States, the European Union, Canada and Australia, shows that although there has been an increase in the global share of women among inventors listed in patent applications from 11% (between 1996-2000) to 14% (between 2011-2015), they remain significantly under-represented among all the countries included in the study. Encouraging and understanding women's engagement in spinout companies is of strategic importance to the UK's new Industrial Strategy which aims to increase investment in science, research and innovation and to support new businesses and growth. Therefore, there is a compelling case for better understanding barriers as well as enabling factors that exists for women scientists, engineers and mathematician in key stages of the spinout process and entrepreneurial activities to commercialise research and innovation. This project vision is to achieve a step change in institutional capabilities to increase the participation of women researchers in STEM disciplines in university spinouts and to mainstream gender in the ecosystem which drives innovation. Our project aims to achieve a step change in institutional capabilities to increase the participation of women scientists, engineers and mathematicians in spinouts through the development of a series of interventions to build their innovative and entrepreneurial skills designed to translate their inventions into spinout companies. The project will last 24 months and be articulated into two stages. Stage one will focus on research to understand the causes of women's under-representation in spinouts, and individuals' self-perception of innovation, drawing from existing methods. The second stage of the project will develop practical solutions for institutions to create inclusive opportunities and overcome the barriers for women who take the journey from research to spinout. Findings from our research and best practice will be shared with EPSRC and the wider community at institutional, sector, department and individual levels. Adaption and delivery of entrepreneurial leadership development will enable women to initiate and lead spinouts, grow innovation, entrepreneurial ambitions, confidence and competencies in women scientists engineers and mathematicians. Our findings will be inspired by role models, career stories and mentoring arrangements with successful women spinout CEOs and Board members.

This is an extension of the Fellowship: 'MathSoMac: the social machine of mathematics', which is an Established Career Fellowship, 2014-2018, EPSRC EP/K040251/2 Mathematics is recognized as a profound intellectual achievement, with impact on many aspects of wealth creation and quality of life, and as unique cultural capital, drawing crowds to exhibitions and public lectures. For centuries, the highest level of mathematics has been seen as an isolated creative activity, to produce a proof of a difficult theorem for review and acceptance by research peers. However, at a remarkable inflexion point, new technology is radically extending the power and limits of individuals. Websites such as the polymath or mathoverflow sites allow researchers to collaborate with each other, and "show their working", so that others outside their specialist field can engage with their research and get early insight into things that might be useful. Now routinely used for verification of hardware and software designs, and in cyber-security, computer proof goes beyond symbolic computation, or numerical simulation, to generate mathematical arguments too complex for humans to grasp, and to check these chains of inference from first principles. These phenomena have typically been viewed as distinct, linked only by their relationship to mathematics. Yet they have many common features, not least, as we showed in the original project, their dependence, ultimately, on human and social issues of mathematical judgement and creativity. In this proposal, to extend our current research, we view these phenomena as a united whole, in which people and computer systems combine into a single problem-solving entity, where individuals interact with each other, and with computers which draw on a single "engine" of computer proof. We call this model of the production and application of mathematics the "social machine of mathematics" based on the new paradigm of "Social machines", identified by Berners-Lee about 20 years ago. We focus on two research questions: === "Beyond Inference": how can we give human mathematicians the benefits of computer proof, while shielding them from its complexity? === " Towards impact: how can we evaluate the impact and cultural capital of foundational research?

Lancaster University (LU) proposes a Centre for Doctoral Training (CDT) to develop international research leaders in statistics and operational research (STOR) through a programme in which cutting-edge industrial challenge is the catalyst for methodological advance. Our proposal addresses the priority area 'Statistics for the 21st Century' through research training in cutting-edge modelling and inference for large, complex and novel data structures. It crucially recognises that many contemporary challenges in statistics, including those arising from industry, also engage with constraint, optimisation and decision. The proposal brings together LU's academic strength in STOR (>50FTE) with a distinguished array of highly committed industrial and international academic partners. Our shared vision is a CDT that produces graduates capable of the highest quality research with impact and equipped with an array of leadership and other skills needed for rapid career progression in academia or industry. The proposal builds on the strengths of an existing EPSRC-funded CDT that has helped change the culture in doctoral training in STOR through an unprecedented level of engagement with industry. The proposal takes the scale and scientific ambition of the Centre to a new level by: * Recruiting and training 70 students, across 5 cohorts, within a programme drawing on industrial challenge as the catalyst for research of the highest quality; * Ensuring all students undertake research in partnership with industry: 80% will work on doctoral projects jointly supervised and co-funded by industry; all others will undertake industrial research internships; * Promoting a culture of reproducible research under the mentorship and guidance of a dedicated Research Software Engineer (industry funded); * Developing cross-cohort research-clusters to support collaboration on ambitious challenges related to major research programmes; * Enabling students to participate in flagship research activities at LU and our international academic partners. The substantial growth in data-driven business and industrial decision-making in recent years has signalled a step change in the demand for doctoral-level STOR expertise and has opened the skills gap further. The current CDT has shown that a cohort-based, industrially engaged programme attracts a diverse range of the very ablest mathematically trained students. Without STOR-i, many of these students would not have considered doctoral study in STOR. We believe that the new CDT will continue to play a pivotal role in meeting the skills gap. Our training programme is designed to do more than solve a numbers problem. There is an issue of quality as much as there is one of quantity. Our goal is to develop research leaders who can innovate responsibly and secure impact for their work across academic, scientific and industrial boundaries; who can work alongside others with different skills-sets and communicate effectively. An integral component of this is our championing of ED&I. Our external partners are strongly motivated to join us in achieving these outcomes through STOR-i's cohort-based programme. We have little doubt that our graduates will be in great demand across a wide range of sectors, both industrial and academic. Industry will play a key role in the CDT. Our partners are helping to co-design the programme and will (i) co-fund and co-supervise doctoral projects, (ii) lead a programme of industrial problem-solving days and (iii) play a major role in leadership development and a range of bespoke training. The CDT benefits from the substantial support of 10 new partners (including Morgan Stanley, ONS Data Science Campus, Rolls Royce, Royal Mail, Tesco) and continued support from 5 existing partners (including ATASS, BT, NAG, Shell), with many others expected to contribute.

Building upon our existing flagship industry-linked EPSRC & MRC CDT in Systems Approaches to Biomedical Science (SABS), the new EPSRC CDT in Sustainable Approaches to Biomedical Science: Responsible and Reproducible Research - SABS:R^3 - will train a further five cohorts, each of 15 students, in cutting-edge systems approaches to biomedical research and, uniquely within the UK, in advanced practices in software engineering. Our renewed goal is to bring about a transformation of the research culture in computational biomedical science. Computational methods are now at the heart of biomedical research. From the simulation of the behaviour of complex systems, through the design and automation of laboratory experiments, to the analysis of both small and large-scale data, well-engineered software has proved capable of transforming biomedical science. Biomedical science is therefore dependent as never before on research software. Industries reliant on this continued innovation in biomedical science play a critical role in the UK economy. The biopharmaceutical and medical technology industrial sectors alone generate an annual turnover of over £63 billion and employ 233,000 scientists and staff. In his foreword to the 2017 Life Sciences Industrial Strategy, Sir John Bell noted that, "The global life sciences industry is expected to reach >$2 trillion in gross value by 2023... there are few, if any, sectors more important to support as part of the industrial strategy." The report identifies the need to provide training in skills in "informatics, computational, mathematical and statistics areas" as being of major concern for the life sciences industry. Over the last 9 years, the existing SABS CDT has been working with its consortium of now 22 industrial and institutional partners to meet these training needs. Over this same period, continued advances in information technology have accelerated the shift in the biomedical research landscape in an increasingly quantitative and predictive direction. As a result, computational and hence software-driven approaches now underpin all aspects of the research pipeline. In spite of this central importance, the development of research software is typically a by-product of the research process, with the research publication being the primary output. Research software is typically not made available to the research community, or even to peer reviewers, and therefore cannot be verified. Vast amounts of research time is lost (usually by PhD students with no formal training in software development) in re-implementing already-existing solutions from the literature. Even if successful, the re-implemented software is again not released to the community, and the cycle repeats. No consideration is made of the huge benefits of model verification, re-use, extension, and maintainability, nor of the implications for the reproducibility of the published research. Progress in biomedical science is thus impeded, with knock-on effects into clinical translation and knowledge transfer into industry. There is therefore an urgent need for a radically different approach. The SABS:R^3 CDT will build on the existing SABS Programme to equip a new generation of biomedical research scientists with not only the knowledge and methods necessary to take a quantitative and interdisciplinary approach, but also with advanced software engineering skills. By embedding this strong focus on sustainable and open computational methods, together with responsible and reproducible approaches, into all aspects of the new programme, our computationally-literate scientists will be equipped to act as ambassadors to bring about a transformation of biomedical research.