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.

The Digital Health Hub for Antimicrobial Resistance (AMR) aims to harness innovative digital technologies to ultimately transform antimicrobial one-health surveillance and antimicrobial stewardship, recognising the interconnectedness of AMR between humans, animals and the environment. The World Health Organization declared AMR - also known as the 'silent pandemic' - a top 10 global public health threat facing humanity. AMR also ranks on the UK Cabinet Office Risk Register and yet despite this recognition, there remains alarmingly low levels of attention and funding for AMR prevention. The 2016 O'Neill Review on Antimicrobial Resistance highlights that by 2050, 10 million lives a year and a cumulative US$100 trillion of economic output are at risk unless action is taken to reduce AMR. Resistant pathogens from animals, humans and food can be cross-transmitted and environmental reservoirs are a potentially important domain in which the mobilisation and transfer of resistant genes occur. Thus, an integrated One Health approach to AMR surveillance and public health action is needed. Moreover, there is growing concern that climate change could increase the risk of emerging and re-emerging infectious diseases. There is growing recognition of the importance of data science and digital health technologies in the fight against AMR, though the field remains in its infancy. The COVID-19 pandemic has dramatically accelerated advances in digital health technologies, driven by unprecedented need, and there is a huge opportunity to leverage these advances for AMR. However, there remain many challenges: poor understanding of one-health needs; data linkage, silos and gaps hinder surveillance; the lack of rapid tests, the lack of public awareness of AMR; digital interventions often do not prioritise user-led design and are not grounded in behaviour change; data privacy, security and ethical issues of bringing together large datasets; health inequalities and the digital divide; the disconnect between early stage research and AMR needs, and lack of understanding of how digital technologies can be commercialised, regulated and integrated into health systems and patient pathways. The Digital Health Hub for AMR brings together a critical mass of Co-Is working across traditional disciplines for AMR, including computer science, biomedical engineering, behavioural social science, environmental science, data visualisation, and clinical and public health research, from five universities, NHS, UK Health Security Agency, Centre for Ecology and Hydrology, charities and industry partners. Our hub vision will be achieved through five objectives: 1. Systems-level needs: To nurture a new culture of cross-sector engagement to accelerate the creation and adoption of digital health innovations for AMR one-health surveillance and antimicrobial stewardship. 2. Skills and Capacity: To grow interdisciplinary skills, capacity, knowledge sharing and leadership needed to deliver a world-leading digital health strategy for combatting AMR. 3. Grand Challenges: To co-create digital health solutions for two AMR grand challenges: i) Digital one-health surveillance of antibiotic use and AMR, linking human, animal and environmental data ii) Digital antimicrobial stewardship via decision support algorithms, digital diagnostics wearables and sensors 4. Partnership Fund: To grow critical mass and a hub of innovation by seeding interdisciplinary pilot studies between industry, academia, health and social care. 5. Impact and Engagement: To maximise hub impact and EPSRC's investment through our communications strategy, patient and public engagement, biannual conferences and events.

Soft Matter is ubiquitous, in the form of polymers, colloids, gels, foams, emulsions, pastes, or liquid crystals; of synthetic or biological origin; as bulk materials or as thin films at interfaces. Soft Matter impinges on almost every aspect of human activity: what we eat, what we wear, the cars we drive, the medicines we take, what we use to keep clean and healthy, in sport and leisure. Soft Matter plays a role in many industrial processes including new frontiers such as digital manufacturing, regenerative medicine and personalised products. Soft Matter is complex chemically and physically with structure and properties that depend on length and time scales. Too often the formulation of soft materials has been heuristic, without the fundamental understanding that underpins predictive design, which hampers innovation and leads to problems in scale up and reformulation in response to changing regulation or customer preferences. Durham, Edinburgh and Leeds Universities set up the SOFI CDT in 2014 in response to the challenge from manufacturers across the personal care, coatings, plastics and food sectors to provide future employees with the skills to transform the design and manufacture of soft materials from an art into a science. The dialogue continues with industrial partners, both old and new, which has resulted in this bid for a refreshed CDT in Soft Matter - SOFI2 - that reflects the evolving scientific, technological and industrial landscape. We have a new partnership with the National Formulation Centre, who will lead a training case study and contribute to the wider training programme, and with many new partners from SMEs to multinationals. We will seek to involve more small and medium-sized companies in SOFI2 by providing opportunities for them to engage in training and project supervision. SOFI2 will have increased training in biological soft matter, which has been identified as a growth area by the EPSRC and our partners, and in scale-up and manufacturing, so that our students can understand better the challenges of taking ideas from the laboratory to the customer. Social responsibility in research and innovation will be embedded throughout the training program and we will trial new ideas in participatory research where the public is involved in the creation of research projects. Each cohort of 16 students will spend their first six months on a common training programme in science and engineering, built around case studies co-delivered with industry partners. They then select their PhD projects and join their research groups in Durham, Leeds or Edinburgh. Generic and transferable skills training continues throughout the four years, bringing the cohorts together for both academic-led and student-led activities. We aim to produce SOFI2 graduates who are business-aware and who are good citizens as well as good scientists. The importance of Soft Matter to the UK economy cannot be understated. Industry sectors relying on Soft Matter include paints and coatings; adhesives, sealants and construction products; rubber, plastics and composite materials; pharmaceuticals and healthcare; cosmetics and personal care; household and professional care; agrochemicals; food and beverages; inks and dyes; lubricants and fuel additives; and process chemicals. A 2018 InnovateUK report estimate the formulated products sector (most of which involves Soft Matter) contributed £149 billion annually to the UK economy. The formulated products sector is undergoing a rapid transformation in response to a shift to sustainable feedstocks, environmental and regulatory pressures and personalised products. It will also be shaped in unpredictable ways by data analytics and artificial intelligence. SOFI2 will equip students with the knowledge and skills to thrive in this business environment.

There is tremendous future scope for biomolecular simulation to provide unprecedented insights into biomolecular systems. The level of detail afforded by these methods, along with their ability to rationalise experimental data and their predictive power are already enabling them to make significant contributions in a wide variety of areas that are crucial for healthcare, quality of life and the environment. The UK biomolecular simulation community has a strong international reputation, with world-leading efforts in in drug design and development, biocatalysis, bionano-technology, chemical biology and medicine. HECBioSim has already delivered outstanding research with impact in bionanotechology, drug design and AMR. But we have only just scratched the surface and there is currently huge room for expansion. Having access to the largest, most modern computing facilities is essential for this. Renewal of the Consortium will enable us to continue allocating time ARCHER for cutting-edge biomolecular simulations. We will place a special emphasis on reaching out to experimentalists and scientists working in industry in order to foster interactions between computational and experimental scientists, and academia and industry to encourage integrated multidisciplinary studies of key problems. Biomolecular simulation and modelling is an integral part of drug design and development. The pharmaceutical industry needs well-trained scientists in this area, as well as the development of new methods (e.g. for prediction of drug binding affinities, ligand selectivity and metabolism). Members of the consortium have a strong track record of collaboration with industry to deliver trained scientists and new methodologies. For example, PhD students trained by consortium members have recently taken up positions in UCB, Unilever, Oxford Nanoimaging and even Sky Broadcasting as software developer. Many of these academic-industry collaborations have been strengthened by work done through HECBioSim allocations. The Consortium will continue to welcome new members from across the whole community. We will continue to develop computational tools and training for both experts and non-experts using biomolecular simulation on HEC resources. We propose to develop new tools that will enable inter-conversion between biomolecular systems at different levels of resolution thereby allowing users to tackle more ambitious 'grand challenges' than are currently feasible. In summary HECBioSim will foster collaborations between computational and experimental scientists between scientists working in industry and academia in all disciplines within biomolecular simulation to maintain the UK as a world-leader in this field.

Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.