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Doctoral Training in Cloud Computing for Big Data

EPSRC Centre for Doctoral Training in Cloud Computing for Big Data

This new multi-million pound initiative will train the next generation of experts in the analysis of "big data" using advanced statistical methodologies and the latest cloud computing technologies, addressing an acute worldwide skills shortage.

Cloud computing provides vast computing resources on-demand. It has become important due to the growth of "big data": the large, complex, datasets now being created in almost all fields of activity, from healthcare to e-commerce. The full potential of cloud computing for extracting knowledge from big data has however rarely been achieved outside a few large companies due to a severe shortage of skilled people. The Newcastle University CDT will address this by producing the multi-disciplinary experts in the statistics and computing science required to extract knowledge from big data.

Fully-funded four-year PhD studentships are available for UK and EU students. The stipend amount is £14,553.

Applications for this round have now closed, please check back at a later date for future deadlines.

We are recruiting students from both Computer Science and Mathematics/Statistics backgrounds and providing an intensive course of interdisciplinary training during Year 1 of the four year PhD programme. All students associated with the CDT will be located together in brand new purpose-built accommodation within Newcastle's new Science Central district. This building will provide state-of-the-art training and Cloud Computing Facilities in an environment which mixes academics, researchers and industry technologists.

Why Join Us?

  • Fully funded places for UK / EU students
  • Don’t learn alone – benefit from the support of a cohort environment
  • Purpose built facilities
  • Access to experts from industry
  • A bespoke curriculum, designed to give you industry ready skills.

More details, including how to apply, are provided at our website:

Cloud Computing for Big Data

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