Digitalisation has generated a new era of technological innovations whose value can only be maximised with equally innovative cyber security. Our specific focus is on the cyber security of digitalisation and data in large-scale, intermeshed systems and infrastructures - where the boundaries between systems are blurred, data distributed with strong localisation and sovereignty claims, and there exist numerous, intricate inter-dependencies between service architectures. With the increasing shortage of cyber security professionals - both globally and in the UK - there is an urgent need for future research leaders who will have the capability to anticipate the challenges and develop innovative solutions to cyber security in a world where technology operates without concrete, clearly delineated digital boundaries. This capability is critical to ensure that digital infrastructures are secure and resilient and security professionals have suitable methods, tools, techniques and insights for securing the digital societal fabric. The Centre for Doctoral Training (CDT) 'Cyber Secure Everywhere: Resilience in a World of Disappearing System Boundaries' will train at least 50 new doctoral-level graduates to address this capability gap. We will do this by educating PhD students in both the technical skills needed to study and analyse blended infrastructures, while simultaneously training them to understand the challenges as fundamentally human too. The training involves close involvement with industry and practitioners who have played a key role in co-creating the programme. The training also leverages state-of-the-art research testbeds and labs at universities of Bristol and Bath as well as partner industry organisations and international research centres. The programme builds on the best practices developed as part of our current CDT on Trust, Identity, Privacy and Security in Large-Scale Infrastructures (TIPS-at-Scale). The first year will involve a series of taught modules providing core knowledge in cyber security (both technical and human & organisational aspects). There will be a programme of co-creation activities with industry as well as deep dives on particular research topics and industry challenges. This co-creation and collaboration ethos will continue throughout their research projects. Throughout the 4-year programme, students will also receive skills training on a number of fundamental computational and analytical techniques as well as intellectual property, entrepreneurship and commercialisation. They will work collaboratively with students in-year and across-years on shared problems and explore responsible innovation in real-world contexts. Through their projects and state-of-the-art experimental infrastructures, they will develop knowledge and expertise on rigorous, evidence-based research on cyber security. The CDT is an exciting, novel way to develop future research and industry leaders who are not only able to tackle cyber security in emerging and future digital infrastructures but can do so in a way that is based on rigorous experimental work and a core ethos of responsible innovation.

DRIVE-Health will train a minimum of 85 PhD health data scientists and engineers with the skills to deliver data-driven, personalised, sustainable healthcare for 2027 and beyond. Co-created with the NHS Trusts, healthcare providers, patients, healthtech, pharma, charities and health data stakeholders in the UK and internationally, it will build on the successes of its King's College London seed-funded and industry-leveraged pilot. Led by an established team, further growing the network of funding partners and collaborators built over the past four years, it will leverage an additional £1.45 of investment from King's and partners for every £1 invested by EPSRC. A CDT in data driven health is needed to deliver the EPSRC Priority for Transforming Health and Healthcare, EPSRC Health Technologies Strategy, and on challenges laid out in the UK Government's 2022 Plan for Digital Health and Social Care envisaging lifelong, joined-up health and care records, digitally-supported diagnoses and therapies, increasing access to NHS services through digital channels, and scaling up digital health self-help. This ambition is made possible by the increasing availability of real-world routine healthcare data (e.g. electronic health care record, prescriptions, scans) and non-healthcare sources (e.g. environmental, retail, insurance, consumer wearable devices) and the extraordinary advances in computational power and methods required to process it, which includes significant innovations in health informatics, data capture and curation, knowledge representation, machine learning and analytics. However, for these technological and data advances to deliver their full potential, we need to think imaginatively about how to re-engineer the processes, systems, and organisations that currently underpin the delivery of healthcare. We need to address challenges including transformation of the quality, speed and scale of multidisciplinary collaborations, and trusted systems that will facilitate adoption by people. This will require a new generation of scientists and engineers who combine technical knowledge with an understanding of how to design effective solutions and how to work with patients and professionals to deliver transformational change. DRIVE-Health's unique cohort-based doctoral research and training ecosystem, embedded across partner organisations, will equip students with specialist skills in five scientific themes co-produced with our partners and current students: (T1) Sustainable Healthcare Data Systems Engineering investigates methods and frameworks for developing scalable, integrated and secure data-driven software systems (T2) Multimodal Patient Data Streams will enable the vision of a highly heterogeneous data environment where device data from wearables, patient-generated content and structured/unstructured information from electronic health records can combine seamlessly (T3) Complex Simulations and Digital Twins focuses on the paradigm of building simulated environments, including healthcare settings or virtual patients, to make step-change advances in individual predictive models and to inform clinical and organisational decision-making. (T4) Trusted Next-Generation Clinical User Interfaces will place usability front and centre to ensure health data science applications are usable in clinical settings and are aligned with users' workflows (T5) Co-designing Impactful Healthcare Solutions, is a cross-cutting theme that ensures co-production and co-design in the context of health data science, engagement with stakeholders, evaluation techniques and achieving maximum impact. The theme training will be complemented with a cohort and programme-wide approach to personal, career, professional and leadership development. Students will be trained by an expert pool of 60+ supervisors from KCL and across partners, delivering outstanding supervision, student mentoring, opportunities, research quality and impact.