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Eight new PhD training centres to boost UK's data science expertise

26 October 2017

Data intensive science in the UK has received a major boost thanks to an investment of almost £10million to train the next generation of experts in this important research area.

The constant advancement of computer technology has had a profound impact on science and industry, making possible some of the most important discoveries in recent years.

Thanks to increasingly powerful technology, researchers can gather, store and utilise vast amounts of data – but to help to make sense of this data, many more expert data scientists are needed.

The UK’s Science and Technology Facilities Council (STFC) is supporting eight new Centres for Doctoral Training (CDT) in data intensive science to address this skills requirement.

The centres include industrial partners – including household names like Aviva, EDF Energy and Hewlett Packard – and will offer comprehensive training in data intensive science through cutting edge research projects and a targeted academic training programme. This will be complemented by secondments to national and international partners.

STFC’s Executive Director of Programmes Professor Grahame Blair said: “This investment will not only bring on the next generation of much-needed data scientists with the skills and knowledge to become leaders in the field, it will be crucial in ensuring the UK research sector and the UK economy remains competitive on the world stage.”

The eight new centres will be based at 19 universities – the Universities of Cambridge, Cardiff/Bristol/Swansea, Durham, Edinburgh/Glasgow/St Andrews, Liverpool/Liverpool John Moores, Manchester /Lancaster/Sheffield, Southampton/Sussex/Portsmouth/Queen Mary/Open and UCL.

The bulk of the funding comes from the £90million allocated for 1,000 new PhD places across all the UK’s Research Councils, announced in the 2017 Spring Budget as part of the National Productivity Investment Fund.

Through this funding, the STFC will be supporting nearly 100 PhD students, who will be trained to analyse data from astrophysics, accelerator science, nuclear or particle physics research, as well as to problems posed by industry and other organisations. They will be supplemented by around 40 additional studentships funded directly through the STFC and other sources.

Professor Blair added: “It is vital that all sectors in this field work together and learn from each other. The investment in these new centres builds on the creation of the World Wide Web at CERN and the big data challenges of both the Large Hadron Collider in our particle physics programme and the large cosmological surveys in our astronomy programme.

“It reinforces the importance that STFC and the UK Government places on having a strong community of research staff with expertise in data intensive science and on tapping this exceptional pool of talent for both frontier research and for interaction with industry.”

Modern observational and experimental facilities produce mountains of data and sifting through that data manually would take years. This is where the data scientists come in.

Data-intensive science utilises sophisticated computational, statistical and programming techniques, including artificial intelligence and machine learning to extract insights from huge datasets to make new discoveries.

Professor Nikos Konstantinidis of UCL’s Department of Physics and Astronomy will be co-directing the university’s CDT. He said: "We are delighted to be part of this exciting STFC initiative. UCL has a long-standing tradition of excellence in data intensive science, with pioneering contributions and leading roles on many international projects in particle physics and astronomy, as well as a strong culture of cross-disciplinary research and collaboration between academia and industry. The UCL Centre will build on these strengths to train the next generation of data science leaders, and to accelerate the development and application of pioneering data intensive science techniques that promise to offer great benefits to the UK economy and to enrich the STFC science programme."

Prof Carsten P Welsch, Head of the University of Liverpool’s Physics Department and Director of the Liverpool CDT, said: “Both the University of Liverpool and Liverpool John Moores University have a long-standing track record in the design and construction of advanced scientific instruments. Both have also developed strong links to many international research laboratories. The PhD students in this new centre will now benefit from this unique expertise and get trained in an area of research that is highly important for both, fundamental science and industry applications.”


Becky Parker-Ellis
STFC Media Officer
Tel: 07808 879294

Notes to Editors

STFC and Data-Intensive Science:
As well as funding education in data intensive science, STFC also has a long history of developing and implementing data intensive scientific services such as the UK component of the Worldwide Large Hadron Collider Computing Grid.

STFC’s Scientific Computing Department is one of the largest scientific computing departments in Europe, delivering expertise in computational science and professional large-scale scientific, data management and computing systems, services and expertise to STFC, national, and international scientific user communities, and to our collaborators and stakeholders in other Research Councils.

The department provides advanced computing facilities at the Rutherford Appleton Laboratory, such as the JASMIN super-data-cluster for environmental data analysis. This is complemented by the STFC Hartree Centre which hosts and operates large-scale computing facilities at the Daresbury Laboratory, such as JADE to support research and industrial applications of machine-learning.

STFC provides these computing infrastructures not only to support the scientific research community, but also to commercial companies in a range of sectors to increase the UK’s scientific and economic impact by the creation of innovative solutions.

STFC Scientific Computing Department

Last updated: 31 October 2017


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