This Hub accelerates progress towards a new "quantum era" by engineering small, high precision quantum systems, and linking them into a network to create the world's first truly scalable quantum computing engine. This new computing platform will harness quantum effects to achieve tasks that are currently impossible. The Hub is an Oxford-led alliance of nine universities with complementary expertise in quantum technologies including Bath, Cambridge, Edinburgh, Leeds, Strathclyde, Southampton, Sussex and Warwick. We have assembled a network of more than 25 companies (Lockheed-Martin, Raytheon BBN, Google, AMEX), government labs (NPL, DSTL, NIST) and SMEs (PureLiFi, Rohde & Schwarz, Aspen) who are investing resources and manpower. Our ambitious flagship goal is the Q20:20 engine - a network of twenty optically-linked ion-trap processors each containing twenty quantum bits (qubits). This 400 qubit machine will be vastly more powerful than anything that has been achieved to date, but recent progress on three fronts makes it a feasible goal. First, Oxford researchers recently discovered a way to build a quantum computer from precisely-controlled qubits linked with low precision by photons (particles of light). Second, Oxford's ion-trap researchers recently achieved a new world record for precision qubit control with 99.9999% accuracy. Third, we recently showed how to control photonic interference inside small silica chips. We now have an exciting opportunity to combine these advances to create a light-matter hybrid network computer that gets the 'best of both worlds' and overcomes long-standing impracticalities like the ever increasing complexity of matter-only systems, or the immense resource requirements of purely photonic approaches. Engineers and scientists with the hub will work with other hubs and partners from across the globe to achieve this. At present proof-of-principle experiments exist in the lab, and the 'grand challenge' is to develop compact manufacturable devices and components to build the Q20:20 engine (and to make it easy to build more). We have already identified more than 20 spin-offs from this work, ranging from hacker-proof communication systems and ultra-sensitive medical and military sensors to higher resolution imaging systems. Quantum ICT will bring great economic benefits and offer technical solutions to as yet unsolveable problems. Just as today's computers allow jet designers to test the aerodynamics of planes before they are built, a quantum computer will model the properties of materials before they've been made, or design a vital drug without the trial and error process. This is called digital quantum simulation. In fact many problems that are difficult using conventional computing can be enhanced with a 'quantum co-processor'. This is a hugely desirable capability, important across multiple areas of science and technology, so much so that even the prospect of limited quantum capabilities (e.g. D-Wave's device) has raised great excitement. The Q20:20 will be an early form of a verifiable quantum computer, the uncompromised universal machine that can ultimately perform any algorithm and scale to any size; the markets and impacts will be correspondingly far greater. In addition to computing there will be uses in secure communications, so that a 'trusted' internet becomes feasible, in sensing - so that we can measure to new levels of precision, and in new components - for instance new detectors that allow us to collect single photons. The hub will ultimately become a focus for an emerging quantum ICT industry, with trained scientists and engineers available to address the problems in industry and the wider world where quantum techniques will be bringing benefits. It will help form new companies, new markets, and grow the UK's knowledge economy.

The EPSRC Centre for Doctoral Training in Statistics and Machine Learning (StatML) will address the EPSRC research priority of the 'physical and mathematical sciences powerhouse' through an innovative cohort-based training program. StatML harnesses the combined strengths of Imperial and Oxford, two world-leading institutions in statistics and machine learning, in collaboration with a broad spectrum of industry partners, to nurture the next generation of leaders in this field. Our students will be at the forefront of advancing the core methodologies of data science and AI, crucial for unlocking the value inherent in data to benefit industry and society. They will be equipped with advanced research, technical, and practical skills, enabling them to make tangible real-world impacts. Our students will be ethical and responsible innovators, championing reproducible research and open science. Collaborating with students, charities and equality experts, StatML will also pioneer a comprehensive strategy to promote inclusivity, attract individuals from diverse backgrounds and eliminate biases. This will help diversify the UK's future statistics and machine learning workforce, essential for ensuring data science is used for public good. Data science and AI are now part of our everyday lives, transforming all sectors of the economy. To future-proof the UK's prosperity and security, it is essential to develop new methodology, specifically tailored to meet the big societal challenges of the future. The techniques underpinning such methods are founded in statistics and machine learning. Through close collaboration with a broad range of industry partners, our cohort-based training will support the UK in producing a critical mass of world-leading researchers with expertise in developing cutting-edge, impactful statistical and machine learning methodology and theory. It is well documented in government and learned society reports that the UK economy has an urgent need for these people. The significant level of industry support for our proposal also highlights the necessity of filling this gap in the UK data science ecosystem. StatML will learn from and build upon our previous successful experiences in cohort training of doctoral students (our existing StatML CDT funded in 2018, as well as other CDTs at Imperial and Oxford). Our students will continue to produce impactful, internationally leading research in statistics and machine learning (as evidenced by our students' impressive publication record and our world-leading research environment, as rated by the REF 2021 evaluation), while complementing this with a bespoke cohort-based Advanced Training program in Statistics and Machine Learning (StatML-AT). StatML-AT has been developed from our experience and in partnership with industry. It will be responsive to emerging technologies and equip our students with the practical skills required to transform how data is used. It will be delivered by our outstanding academics from both institutions alongside with industry leaders to ensure that students receive training in cutting edge technologies, along with the latest ideas in ethics, responsible innovation, sustainability and entrepreneurship. This will be complemented by industrial and academic placements to allow the students to develop their own international network and produce high-impact research. Together, StatML and its partners will train 90+ students over 5 cohorts. More than half of these will be funded from external sources, including 25+ by industry, representing excellent value for money. Our diverse cohorts will benefit from a unique and responsive training program combining academic excellence, industry engagement, and interdisciplinary culture. This will make StatML a vibrant research environment inspiring the next methodological advancements to transform the use of data and AI across industry and society.