“A unique and timely training context and outlook that will nurture PhD researchers who can ensure applications of big data and machine intelligence are underpinned by innovations that prioritise human values, experience and capabilities. We will invert the science-first convention— which moves from fundamentals to applications—to a people-first approach that starts with challenging contexts to disrupt and direct new, adventurous and exciting computational science.” Professor Matt Jones, Director of the Centre for Doctoral Training.
The EPSRC Centre for Doctoral Training in Enhancing Human Interactions and Collaborations with Data and Intelligence Driven Systems is based within the Computational Foundry.
Join our People-First Movement and Change the World
You do not need to look far for evidence that highlights widespread and growing concerns around the coming transformations promised by big data and artificial intelligence.
There is a darkness descending on and through the digital and our Centre is a beacon of light, with a fresh and passionate outlook that provides insights recognised globally and works to attract diverse groups of PhD researchers, stakeholders and community members to co-create a better future. There are great examples of how data-driven and intelligent systems can be hugely positive for society; our Centre will help realise such hopes by grounding them in the rich messiness of human life and aspirations.
We address a clear and challenging need to put people at the heart of research and innovation for data-driven and intelligent technologies. A need valued by our external partners who include Admiral Group, Tata Steel, Ford, Fujitsu, McAfee, Google, NHS and Facebook.
While there will be many, often essential, initiatives to train computational researchers in terms of fundamental data analytics and AI algorithms and processes, our Centre will foster breakthroughs in core aspects of computational science that can enhance the human experience of and engagement with data and intelligence in challenging contexts by exposing and disrupting the science to and by their demands.