The EPSRC CDT in Net Zero Aviation in partnership with Industry will collaboratively train the innovators and researchers needed to find the novel, disruptive solutions to decarbonise aviation and deliver the UK's Jet Zero and ATI's Destination Zero strategies. The CDT will also establish the UK as an international hub for technology, innovation and education for Net Zero Aviation, attracting foreign and domestic investment as well as strengthening the position of existing UK companies. The CDT in Net Zero Aviation is fully aligned with and will directly contribute to EPSRC's "Frontiers in Engineering and Technology" and "Engineering Net Zero" priority areas. The resulting skills, knowledge, methods and tools will be decisive in selecting, integrating, evaluating, maturing and de-risking the technologies required to decarbonise aviation. A systems engineering approach will be developed and delivered in close collaboration with industry to successfully integrate theoretical, computational and experimental methods while forging cross theme collaborations that combine science, technology and engineering solutions with environmental and socio-economic aspects. Decarbonising aviation can bring major opportunities for new business models and services that also requires a new policy and legislative frameworks. A tailored, aviation focused training programme addressing commercialisation and route to market for the Net Zero technologies, operations and infrastructure will be delivered increasing transport and employment sustainability and accessibility while improving transport connectivity and resilience. Over the next decade innovative solutions are needed to tackle the decarbonisation challenges. This can be only achieved by training doctoral Innovation and Research Leaders in Net Zero Aviation, able to grasp the technology from scientific fundamentals through to applied engineering while understanding the associated science, economics and social factors as well as aviation's unique operational realities, business practices and needs. Capturing the interdependencies and interactions of these disciplines a transdisciplinary programme is offered. These ambitious targets can only be realised through a cohort-based approach and a consortium involving the most suitable partners. Under the guidance of the consortium's leadership team, students will develop the required ethos and skills to bridge traditional disciplinary boundaries and provide innovative and collaborative solutions. Peer to peer learning and exposure to an appropriate mix of disciplines and specialities will provide the opportunity for individuals and interdisciplinary teams to collaborate with each other and ensure that the graduates of the CDT will be able to continually explore and further develop opportunities within, as well as outside, their selected area of research. Societal aspects that include public engagement, awareness, acceptance and influencing consumer behaviour will be at the heart of the training, research and outreach activities of the CDT. Integration of such multidisciplinary topics requires long term thinking and awareness of "global" issues that go beyond discipline and application specific solutions. As such the following transdisciplinary Training and Research Themes will be covered: 1. Aviation Zero emission technologies: sustainable aviation fuels, hydrogen and electrification 2. Ultra-efficient future aircraft, propulsion systems, aerodynamic and structural synergies 3. Aerospace materials & manufacturing, circular economy and sustainable life cycle 4. Green Aviation Operations and Infrastructure 5. Cross cutting disciplines: Commercialisation, Social, Economic and Environmental aspects 75 students across the UK, from diverse backgrounds and communities will be recruited.

AI and Machine Learning often address challenges that are relatively monolithic in nature: determine the safest route for an autonomous car; translate a document from English to French; analyse a medical image to detect a cancer; answer questions about a difficult topic. These kinds of challenge are very important and worthwhile targets for AI research. However, an alternative set of challenges exist that are more *collective* in nature and that unfold in *real time*: - help minimise the impact of a pandemic sweeping through a population of people by informing the coordination of local and national testing, social distancing and vaccination interventions; - predict and then monitor the extent and severity of an extreme weather event using multiple real-time physical and social data streams; - anticipate and prevent a stock market crash caused by the interactions between many automated trading agents each following its own trading algorithm; - derive city-wide patterns of changing mobility from high-frequency time series data and use these patterns to drive city planning decisions that maximise liveability and sustainability in the future city; - assist populations of people with type 2 diabetes to avoid acute episodes and hospitalisation by identifying patterns in their pooled disease trajectories while preserving their privacy and anonymity. Developing AI systems for these types of problem presents unique challenges: extracting reliable and informative patterns from multiple overlapping and interacting data streams; identifying and controlling for inherent biases within the data; determining the local interventions that can allow smart agents to influence collective systems in a positive way; developing privacy preserving machine learning and advancing ethical best practices for collective AI; embedding novel machine learning and AI in portals, devices and tools that can be used transparently and successfully by different types of user. The AI for Collective Intelligence (AI4CI) Hub will address these challenges for AI in the context of critically important real world use cases (cities, pandemics, health care, environment and finance) working with key stakeholder partners from each sector. In addition to significantly advancing applied AI research for collective intelligence, the AI4CI Hub will also work to build *community* in this research area, linking together academic research groups across the UK with each other and with key industry, government and public sector organisations, and to build *capability* by developing and releasing open access training materials, tools, demonstrator systems and best practice guidance, and by supporting the career development of early and mid-career researchers both within academia and beyond. The AI for Collective Intelligence Hub will be a centre of gravity for a nation-wide research effort applying new AI to collective systems.

"Semiconductors" are synonymous with "Silicon chips". After all Silicon supported computing technologies in the 20th century. But Silicon is reaching fundamental limits and already many of the technologies we take for granted are only possible because of Compound Semiconductors (CS). These include: the internet, smart phones and energy-efficient LED lighting! CSs are also at the heart of most of the new technologies envisaged, including 6G wireless, ultra-high speed optical fibre connectivity, LIDAR for autonomous vehicles, high voltage switching for electric vehicles, the IoT and high-capacity data storage. CSs also offer huge opportunities for energy efficiency and net zero. The CS Hub will contribute to "Engineering Net Zero", through products, such as energy-efficient electronics, and by introducing new environmentally-friendly manufacturing processes; to "Quantum Technologies", by creating practical implementations that can be manufactured at scale; to the "Physical and Mathematical Sciences Powerhouse" and "Frontiers in Engineering and Technology", through e.g. cutting-edge materials science and manufacturing-process innovation. CS materials are grown atom-by-atom on slices of crystalline material, known as substrates, which provide mechanical support for the resulting "wafer" during the next stage of fabrication. CSs are often made on relatively small substrates. Manufacturers have had to combine functions by assembling discrete devices but this is expensive. New approaches to integration in epitaxy and fabrication are required along with wafer-size scale-up for the new applications. Applications such as in quantum technology (QT) are pushing requirements for more accurate and highly reproducible manufacturing-processes. With such improvements CS will underpin the UK quantum industry and enable impact for the existing QT investments. We will create designs that are more tolerant to typical variations that occur during manufacturing; develop manufacturing processes that are more uniform and repeatable; create techniques to characterise performance part-way through manufacturing, create techniques to combine materials (e.g. CS grown atom-by-atom on Silicon) and combine functions on chip. We will study and implement ways to make CS manufacturing more environmentally friendly. We will make it easier to compare the environmental foot-print of different CS research and manufacturing-processes by making available relevant, high quality data in the form of accessible libraries of the resource and energy usage of the feedstocks and processes used in CS manufacturing. We aim to change the mind-set of UK academics. Our vision is that researchers think about the translation of their research from the beginning of the innovation process and about the requirements that next generation product manufacturers will face. As a critical factor in all future manufacturing, we aim to embed the philosophy of resource efficiency of the research itself, resource efficiency of the manufacturing process, as well as of the application it supports. We aim to repatriate and connect CS manufacturing supply chains to re-shore production and facilitate innovation, enabling development of holistic solutions. We will address the current staffing shortages of the CS industry by: providing leadership in improving career structure and enhancing training for Hub research and technical staff; putting in place the very best ED&I practice to create the most positive and inclusive working environment and promulgating this across the industry; inspiring the next generation of the CS workforce as well as spreading the news about the fantastic career opportunities currently available. By working closely with industry partners on all these aspects we will attract and retain staff in this critical UK manufacturing industry.