UK/EU students

MRes plus PhD studentships - Cloud Computing for Big Data (EPSRC Centre for Doctoral Training)

Value of award

EPSRC minimum stipend (currently £14,553 per annum for 2017 entry) and full fees paid for UK/EU students. There is a further £2,000 per annum for travel and consumables. A laptop is provided for your studies.

Number of awards


Start date and duration

September 2018 for 4 years.

Application closing date

30 November 2017, 31 January 2018 (then rolling closing dates until all places are filled).


Data science is an exciting new inter-disciplinary field driving almost every area of science, engineering and commerce.

The EPSRC Centre for Doctoral Training (CDT) in Cloud Computing for Big Data will enable you to develop deep technical expertise and apply your knowledge to problems in application areas for which you have a passion. 

This four year programme (MRes plus PhD) 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 you move on to your 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:

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, you will carry out PhD research, guided by PhD supervisors from within the centre, and typically additional advisors from industry. The CDT is 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 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). You will also have the opportunity to present your ongoing research work, and obtain constructive feedback from leading experts in a friendly and informal environment. 


EPSRC / Newcastle University / Red Hat / Microsoft / Akzo Nobel

Name of supervisor(s)

N/A – research area decided during MRes year.

Eligibility Criteria

2:1 in computing, mathematics, statistics or other numerate disciplines.

The studentships are open to applicants satisfying EPSRC home/UK or EU fee status criteria (, who are eligible for home fees.

We also welcome applications from students from outside the UK who have already secured full scholarship funding from other sources (eg from the National Government of the home country of the student).

How to apply

You must apply through the University’s online postgraduate application system. To do this please ‘Create a new account’.

Under the ‘Programme of Study’ tab enter the course code: 4852F in the 'Programme Code' field and ‘search’ - then select 'Master of Research in Cloud Computing for Big Data'.

In your online application, please include your CV and a personal statement. This should be no longer than 500 words in length. It should clearly communicate why you are interested in conducting research in Cloud Computing for Big Data. A good personal statement should articulate how your prior experience or qualifications provide a good foundation for conducting a PhD within our CDT in Cloud Computing for Big Data, and state what new skills and expertise you hope to develop through our PhD training programme. We would also like you to tell us why you are motivated to conduct a PhD.


Please email

Eligible Courses