Details of Grant 

EPSRC Reference:	EP/S022074/1
Title:	UKRI Centre for Doctoral Training in Environmental Intelligence: Data Science & AI for Sustainable Futures
Principal Investigator:	Williams, Professor HTP
Other Investigators:	Hopkinson, Professor P Lenton, Professor TM Arribas, Professor A Leonelli, Professor S Williams, Professor H Everson, Professor R Challenor, Professor P Hartley, Professor SA Fleming, Professor LE
Researcher Co-Investigators:
Project Partners:	Amazon Web Services (Not UK) EDF Exeter City Futures IBM UK Ltd Met Office Microsoft Oasis Loss Modelling Framework Ltd Office for National Statistics Ordnance Survey The UK Hydrographic Office World Health Organisation (WHO)
Department:	Mathematics
Organisation:	University of Exeter
Scheme:	Centre for Doctoral Training
Starts:	01 June 2019	Ends:	30 November 2027	Value (£):	5,468,643
EPSRC Research Topic Classifications:	Information & Knowledge Mgmt
EPSRC Industrial Sector Classifications:	Environment Energy Information Technologies
Related Grants:
Panel History:	Panel Date Panel Name Outcome 07 Nov 2018 UKRI Centres for Doctoral Training AI Interview Panel U – November 2018 Announced
Summary on Grant Application Form
The vision of this CDT is to enhance society's resilience to changes in our environment through the development of Environmental Intelligence (EI): using the integration of data from multiple inter-related sources and Artificial Intelligence (AI) to provide evidence for informed decision-making, increase our understanding of environmental challenges and provide information that is required by individuals, policy-makers, institutions and businesses. Many of the most important problems we face today are related to the environment. Climate change, healthy oceans, water security, clean air, biodiversity loss, and resilience to extreme events all play a crucial role in determining our health, wealth, safety and future development. The UN's 2030 Agenda for Sustainable Development calls for a plan of action for people, planet and prosperity, aiming to take the bold and transformative steps that are urgently needed to shift the world onto a sustainable and resilient path. Developing a clear understanding of the challenges and identifying potential solutions, both for ourselves and our planet, requires high quality, accessible, timely and reliable data to support informed decision making. Beyond the quantification of the need for change and tracking developments, EI has another important role to play in facilitating change through integration of cutting edge AI technology in energy, water, transport, agricultural and other environmentally-related systems and by empowering individuals, organisations and businesses through the provision of personalized information that will support behavioural change. Students will receive training in the range of skills they will require to become leaders in EI: (i) the computational skills required to analyse data from a wide variety of sources; (ii) environmental domain-specific expertise; (iii) an understanding of governance, ethics and the potential societal impacts of collecting, mining, sharing and interpreting data, together with the ability to communicate and engage with a diverse range of stakeholders. The training programme has been designed to be applicable to students with a diverse range of backgrounds and experiences. Graduates of the CDT will be equipped with the skills they need to become tomorrow's leaders in identifying and addressing interlinked, social, economic and environmental risks. Having highly trained individuals with a wide range of expertise, together with the skills to communicate with a diverse range of stakeholders and communities, will have far reaching impact across a wide number of sectors. Traditionally, PhD students trained in the technical aspects of AI have been distinct from those trained in policy and business implementation. This CDT will break that mould by integrating students with a diverse range of backgrounds and interests and providing them with the training, in conjunction with external partners, that will ensure that they are well versed in both cutting edge methodology and on the ground policy and business implementation. The University of Exeter's expertise in inter- and trans-disciplinary environmental, climate, sustainability, circular economy and health research makes it uniquely placed to lead an inter-disciplinary CDT that will pioneer the use of AI in understanding the complex interactions between the environment, climate, natural ecosystems, human social and economic systems, and health. Students will benefit from the CDTs strong relationships with its external partners, including the Met Office. Many of these partners are employers of doctoral graduates in AI and see an increasing need for employees with skills from across multiple disciplines. Their involvement in the planning and ongoing management of the CDT will ensure that, in this rapidly changing domain, the CDT delivers leading-edge research that will enable partners and others to participate effectively in EI and lead to optimal employment opportunities for its graduates.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Sectors submitted by the Researcher
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Further Information:
Organisation Website:	http://www.ex.ac.uk