The EPSRC Centre for Doctoral Training in Cloud Computing for Big Data is an innovative and highly prestigious programme, offering around 11 students per year the opportunity to study for a PhD in an exciting, new area in which there is an acute skills shortage.
Cloud computing offers the ability to acquire vast, scalable computing resources on-demand. It is revolutionising the way in which data is stored and analysed. The dynamic, scalable approach to analysis offered by cloud computing has become important due to the growth of “big data”: the very large, often complex, datasets now being created in almost all fields of activity, from healthcare to e-commerce. Unfortunately, due to a lack of expertise, the full potential of cloud computing for extracting knowledge from big data has rarely been achieved outside a few large companies; as a result, many organisations fail to realize their potential to be transformed through extracting more value from the data available to them. UK industry faces a huge skills gap in this area as the demand for big data staff has risen exponentially over the past five years from 400 advertised vacancies in 2007 to almost 4,000 in 2012. In addition, the demand for big data skills will continue to outpace the demand for standard IT skills, with big data vacancies forecast to increase by around 18% per annum in comparison with 2.5% for IT. Over the next five years this equates to a 92% rise in the demand for big data skills with around 132K new jobs being created in the UK (e-skills UK, Jan 2013).
While characteristics such as size, data dependency and the nature of business activity will affect the potential for organisations to realise business benefits from big data, organisations don’t have to be big to have big data issues. The problems and benefits are as true for many SMEs as they are for big business which, inevitably broadens and increases the demand for cloud and big data skills. Further, even when security concerns prevent the use of external “public” clouds for certain types of data, organisations are applying the same approaches to their own internal IT resources, using virtualisation to create “private” clouds for data analysis. Discussions with industry have reinforced our view that addressing these challenges requires expert practitioners who can bridge between the design of scalable algorithms, and the underlying theory in the modelling and analysis of data. It is perhaps not surprising that these skills are in short supply: traditional undergraduate and postgraduate courses produce experts in one or the other of these areas, but not both. Newcastle University has been awarded the EPSRC Centre for Doctoral Training in Cloud Computing for Big Data in order to fill this important gap. It will produce multi-disciplinary experts in the mathematics, statistics and computing science of extracting knowledge from big data, with practical experience in exploiting this knowledge to solve problems across a range of application domains.
Directed by Prof Paul Watson and Prof Darren Wilkinson, and delivered jointly by the University's Schools of Computing Science and Mathematics and Statistics, the CDT contains both Computing Scientists and Statisticians working together on challenging problems in this exciting area.
This four year programme adopts an interdisciplinary research philosophy that will build upon your previous background, combining professional and technical skills training with industry-focussed research.
The first year provides advanced Masters level training in cloud computing and data analytics before students move on to their PhD project. Training will begin with a short "crash course" in either Computing science for mathematicians (for the Statistics stream) or Statistics for computing scientists (for the Computing Science stream). Students will then be taught as a unified cohort in topics including Statistics for big data, Programming for big data, Cloud computing, Machine learning, Big data analytics and Time series analysis. The taught component will finish with a substantial group project, with students from different backgrounds working on a practical industry focused data analysis problem. Following this, and in years 2-4, students will carry out PhD research, guided by PhD supervisors from within the centre, and typically additional advisors from industry. The CDT will be located alongside high tech industry and commerce in custom accommodation on the University's new Science Central site.
The CDT is supported by many industrial partners worldwide. Many of the main research projects available for selection will be problems motivated by our industrial partners, and will include the opportunity to work at the industrial partner for a short placement. The CDT also has strong academic links with international groups having a similar vision, including Berkeley's AMPLab and PUCRS in Brazil. A limited number of students will have the opportunity to take part in an exchange programme with our academic partners.
Two-day off-site retreats will take place every 6 months, involving all CDT students as well as supervisors and guest speakers (including industry partners and senior academics). Students will also have the opportunity to present their ongoing research work, and obtain constructive feedback from leading experts in a friendly and informal environment.