We live in an information age, when computers and the software that drives them permeate every aspect of our society. There are two fundamentally important aspects of computation. - One concerns the resources needed to perform computational tasks: how many computational steps are needed, how much computer memory, etc. - The other concerns our ability to master the staggering complexity of the computer systems we create and use. The only way of managing this complexity is to use principles of modularity and abstraction, so that at each step of our design and construction of the system, we see only a very limited piece, whose complexity we can master. While the study of each of these aspects of computing has been greatly advanced as computer science has developed, currently we have a very limited understanding of how they relate to each other. Building on our previous work, this project aims to greatly enhance our common understanding of these issues, and to develop new mathematical tools and methods for studying computation based on this. This can lead in turn to new possibilities for fundamental advances in the field.

Quantum Technologies (QT) are at a pivotal moment with major global efforts underway to translate quantum information science into new products that promise disruptive impact across a wide variety of sectors from communications, imaging, sensing, metrology, simulation, to computation and security. Our world-leading Centre for Doctoral Training in Quantum Engineering will evolve to be a vital component of a thriving quantum UK ecosystem, training not just highly-skilled employees, but the CEOs and CTOs of the future QT companies that will define the field. Due to the excellence of its basic science, and through investment by the national QT programme, the UK has positioned itself at the forefront of global developments. There have been very recent major [billion-dollar] investments world-wide, notably in the US, China and Europe, both from government and leading technology companies. There has also been an explosion in the number of start-up companies in the area, both in the UK and internationally. Thus, competition in this field has increased dramatically. PhD trained experts are being recruited aggressively, by both large and small firms, signalling a rapidly growing need. The supply of globally competitive talent is perhaps the biggest challenge for the UK in maintaining its leading position in QT. The new CDT will address this challenge by providing a vital source of highly-trained scientists, engineers and innovators, thus making it possible to anchor an outstanding QT sector here, and therefore ensure that UK QT delivers long-term economic and societal benefits. Recognizing the nature of the skills need is vital: QT opportunities will be at the doctoral or postdoctoral level, largely in start-ups or small interdisciplinary teams in larger organizations. With our partners we have identified the key skills our graduates need, in addition to core technical skills: interdisciplinary teamwork, leadership in large and small groups, collaborative research, an entrepreneurial mind-set, agility of thought across diverse disciplines, and management of complex projects, including systems engineering. These factors show that a new type of graduate training is needed, far from the standard PhD model. A cohort-based approach is essential. In addition to lectures, there will be seminars, labs, research and peer-to-peer learning. There will be interdisciplinary and grand challenge team projects, co-created and co-delivered with industry partners, developing a variety of important team skills. Innovation, leadership and entrepreneurship activities will be embedded from day one. At all times, our programme will maximize the benefits of a cohort-based approach. In the past two years particularly, the QT landscape has transformed, and our proposed programme, with inputs from our partners, has been designed to reflect this. Our training and research programme has evolved and broadened from our highly successful current CDT to include the challenging interplay of noisy quantum hardware and new quantum software, applied to all three QT priorities: communications; computing & simulation; and sensing, imaging & metrology. Our programme will be founded on Bristol's outstanding activity in quantum information, computation and photonics, together with world-class expertise in science and engineering in areas surrounding this core. In addition, our programme will benefit from close links to Bristol's unique local innovation environment including the visionary Quantum Technology Enterprise Centre, a fellowship programme and Skills Hub run in partnership with Cranfield University's Bettany Centre in the School of Management, as well as internationally recognised incubators/accelerators SetSquared, EngineShed, UnitDX and the recently announced £43m Quantum Technology Innovation Centre. This will all be linked within Bristol's planned £300m Temple Quarter Enterprise Campus, placing the CDT at the centre of a thriving quantum ecosystem.

Quantum technology will revolutionise many aspects of life and bring enormous benefits to the economy and society. The Centre for Doctoral Training in Quantum Informatics (QI CDT) will provide advanced training in the structure, behaviour, and interaction of quantum hardware, software, and applications. The training programme spans computer sciences, mathematics, physics, and engineering, and will enable the use of quantum technology in a way that is integrable, interoperable, and impactful, rather than developing the hardware itself. The training programme targets three research challenges with a strong focus on end user impact: (i) quantum service architecture concerns how to design quantum networks and devices most usefully; (ii) scalable quantum software is about feasible application at scale of quantum technology and its integration with other software; and (iii) quantum application analysis investigates how quantum technology can be used most advantageously to solve end user problems. The QI CDT will offer 75+ PhD students an intensive 4-year training and research programme that equips them with the skills needed to tackle the research challenges of quantum informatics. This new generation will be able to integrate quantum hardware with high-performance computing, design effective quantum software, and apply this in a societally meaningful way. The QI CDT brings together a coalition with national reach including over 65 academic experts in quantum informatics from five universities - the University of Edinburgh, the University of Oxford, University College London, Heriot-Watt University, and the University of Strathclyde - and three public sector partners - the National Quantum Computing Centre, the National Physical Laboratory, and the Hartree Centre. A network of over 30 industry partners, diverse in size and domain expertise, and 9 leading international universities, give students the best basis for meaningful and collaborative research. A strong focus on cohort-based training will make QI CDT students into a diverse network of future leaders in Quantum Informatics in the UK.

In the UK, 3 million children are living with a parent with depression or anxiety. These children are 3 times more likely to develop a mental health problem themselves, putting them at risk of later unemployment, physical health problems, and early mortality. This intergenerational cycle of mental illness is partly because children inherit genetic susceptibility to mental illness from their parents, but largely because of the environmental effects of living with a mentally unwell parent. To prevent future generations of children from developing mental illness and experiencing life-limiting consequences, we urgently need to understand how to break this intergenerational cycle. My research will address this by identifying environmental factors that affect whether mental health problems are passed on from parents to children. For example, I will test whether socioeconomic advantage (such as high family income and high levels of parental education) can interrupt the intergenerational cycle of mental health problems. I will also test whether the intergenerational cycle of mental illness is perpetuated by adverse family environments (e.g., child maltreatment, parental conflict, or parent substance abuse), and mitigated by positive social relationships (e.g., family social support, parent-child bond). To answer these questions, I will use large datasets of parents and children from the UK, Norway, Denmark, and the USA. My specific focus will be on parental depression and anxiety (the most common parental disorders) and their effects on child emotional and behavioural problems, which are well established. I will apply cutting-edge research designs and statistical techniques that can show whether environmental factors causally affect the intergenerational cycle of mental illness. For example, to understand the impact of income, I will test whether a cash-transfer intervention reduces the likelihood that parental mental illness is passed onto children. And to understand the impact of parental education, I will test whether the association between parent and child mental illness is mitigated when parents complete extra years of education due to a national education reform policy. These are just two examples of many methods that I will use to examine the causal effects of environmental factors on the intergenerational cycle of mental illness. By examining whether the findings are similar across different research methods, I will draw robust conclusions about which environmental factors can break the intergenerational cycle of mental illness. Crucially, I will use my findings to highlight modifiable targets for interventions to break the intergenerational cycle of mental illness. For example, if high income is found to mitigate the effects of parent mental illness on children's mental health, then economic interventions such as cash-transfers, tax-breaks, or an increased living wage could be employed to prevent at-risk children from developing mental illness. In addition, if unsafe family environments help explain the impact of transmission, then interventions to improve the family environment such as parenting support programmes could be adopted to help break the intergenerational cycle. To ensure that this research has societal impact, I will involve non-academic partners throughout the project, including policymakers from the Department of Health, clinicians, practitioners, and charities. I will also involve young people with lived experience of personal/parental mental illness throughout the research, to ensure benefit for patients. To share findings and co-design interventions to interrupt intergenerational transmission, I will hold a policy workshop with key stakeholders. I will also work with the Centre for Mental Health to conduct an economic evaluation on the cost effectiveness of interventions to interrupt transmission, and present findings to policymakers to convince them to invest in preventative interventions.

Biocultural heritage - the physical remains of ancient humans, animals, plants and landscapes, as well as material and visual culture - is an important resource. It represents tangible evidence for human interactions with the natural world, biodiversity, food systems, human-animal-environmental health, and exploitation of organic raw materials. As such, there is a growing recognition that interdisciplinary studies of biocultural heritage can help address modern global challenges, all of which are fundamentally cultural with deep histories. Yet biocultural heritage is a finite resource and one that is under threat. At the landscape scale, climate change is endangering heritage sites. Museum collections are being impacted by the curation crisis, which is seeing materials refused accession or deaccessioned without record. But there is also a significant threat to biocultural heritage from the research practices of scientists themselves. Advances in archaeological science are seeing increasing quantities of material targeted for destructive analyses (e.g. aDNA, proteomics, isotopes, radiocarbon dating, organic residue analysis, and histology). Whilst such individual analyses generate transformative results, our networks and research partners (including national institutions, museum curators, archives, community archaeology groups and commercial units) have raised ethical issues associated with the destruction of biocultural heritage. They have highlighted the overwhelming need for: 1) specimens to be preserved by 3D record; 2) scans to be made available for future analyses; 3) data from destructive analysis to be linked to 3D records in a way that is accessible to curators and broader research communities both in the UK and abroad. The last is particularly important to ensure that materials are not repeatedly sampled by different research groups and so that independent lines of evidence can be brought together. To address these issues of collections preservation, storage and accessibility the Biocultural HIVE will: Upgrade our existing physical archive space to better accommodate our own nationally important biocultural collections and provide appropriate environmentally controlled temporary storage for materials being analysed by our CResCa-funded digital imaging facility, SHArD-3D. 2. Create a new laboratory space so that researchers can access, and have space to study, our permanent and temporary collections. 3. Collate and standardise the large quantities of 3D and analytical data from our SHArD-3D collaborations and international UKRI, Wellcome Trust and ERC projects. 4. Use the data generated by point 3) to create and test an open-access, continuously updateable, digital repository (rather than closed-dataset repositories e.g. Archaeology Data Service) for the curation and sharing of digital 3D files and other analytical results. 5. Drawing on expertise from the UKRI funded GLAM-E we will embed ethical data practices into our digital platforms and co-create appropriate open-access policies with our partners. 6. Employ a Database Manager to 1) liaise with stakeholders and 2) populate and maintain the repository with the ultimate intention of migrating it to the RICHeS Digital Research Service at Daresbury, so that it is sustainable beyond the life of the project. This resource will benefit the heritage science community and provide researchers with the ability to deposit, update, and access collections/data on an unprecedented scale. Beyond this it will create a new research platform for data mining, the application of deep-learning technologies, and ensure we are delivering world-leading heritage science.