Study modes: Full-time
Programme website: EPSRC Centre for Doctoral Training in Data Science
Data science is the study of the computational principles and systems for extracting knowledge from data, for maintaining data, and for ensuring its quality. Large data sets are now generated by almost every activity in science, society and commerce.
This EPSRC-sponsored programme tackles the question: how can we efficiently find patterns in these vast streams of data?
Many research areas in informatics are converging on the problem of data science. Those represented in the School include machine learning, artificial intelligence, databases, data management, optimization and cluster computing; and also the unstructured data issues generated in areas such as natural language processing and computer vision.
Our programme will allow you to specialise and perform advanced research in one of these areas, while gaining breadth and practical experience throughout data science.
A short sample of our research interests includes:
Many more topics can be found by exploring the Centre’s web pages, particularly the personal web pages of the Centre supervisors:
You will be supervised by one of our 58 world-renowned faculty. You will also benefit from interacting with a group of 35 leading industrial partners, including Amazon, Apple, Google, IBM, and Microsoft.
This will ensure your research is informed by real world case studies and will provide a source of diverse internship opportunities. Moreover we believe that key research insights can be gained by working across the boundaries of conventional groupings.
We link to the latest information available. Please note that this may be for a previous academic year and should be considered indicative.
|MScR||Data Science||1 Year||Full-time||Programme structure 2017/18|
The MScR is the first part of a longer 1+3 (MSc by Research + PhD) programme offered by the School through the EPSRC.
Our four-year PhD programme combines masters level coursework and project work with independent PhD-level research.
In the first year, you will undertake six masters level courses, spread throughout machine learning, databases, statistics, optimization, natural language processing, and related areas. You will also undertake a significant introductory research project. (Students with previous masters-level work in these areas may request to take three courses and a larger project, instead of six courses.)
At the end of the first year, successful students will be awarded an MSc by Research. From this basis, the subsequent three years will be spent developing and pursuing a PhD research project, under the close supervision of your primary and secondary supervisors.
You will have opportunities for three to six month internships with leading companies in your area, and to participate in our industrial engagement programme, exchanging ideas and challenges with our sponsor companies.
Throughout your studies, you will participate in our regular programmes of seminars, short talks and brainstorming sessions, and benefit from our pastoral mentoring schemes.
The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.
Our research groups contain a diverse range of compute clusters for compute and data-intensive work, including a large cluster hosted by the Edinburgh Compute and Data Facility.
More broadly, the award-winning Informatics Forum is an international research facility for computing and related areas. It houses more than 400 research staff and students, providing office, meeting and social spaces.
It also contains two robotics labs, an instrumented multimedia room, eye-tracking and motion capture systems, and a full recording studio amongst other research facilities. Its spectacular atrium plays host to many events, from industry showcases and student hackathons to major research conferences.
Nearby teaching facilities include computer and teaching labs with more than 250 machines, 24-hour access to IT facilities for students, and comprehensive support provided by dedicated computing staff.
Among our entrepreneurial initiatives is Informatics Ventures, set up to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.
We intend for our graduates to become the research leaders, both in industry and academia, whose work will lead the way in data science. This vision is shared by our industrial supporters, whose support for our internship programme indicates their strong desire to find highly qualified new employees.
You will be part of a new generation of data scientists, with the technical skills and interdisciplinary awareness to become R&D leaders in this emerging area.
Our component research groups already have excellent track-records in post-graduation destinations, including the research labs of industry-leading companies, and post-doctoral research positions in top tier universities.
A UK 2:1 honours degree, or its international equivalent, in computer science, mathematics, physics, engineering or a related discipline.
Applicants coming directly from a bachelors or masters degree are welcome.
Check whether your international qualifications meet our general entry requirements:
All applicants must have one of the following qualifications as evidence of their English language ability:
an undergraduate or masters degree, that was taught and assessed in English in a majority English speaking country as defined by UK Visas and Immigration
Degrees taught and assessed in English must be no more than two and a half years old at the beginning of your degree programme. Language tests must be no more than two years old at the beginning of your degree programme.
Find out more about our language requirements:
If you are not an EU, EEA or Swiss national, you may need an Academic Technology Approval Scheme clearance certificate in order to study this programme.
Find out more about tuition fees and studying costs:
Find out more about scholarships and funding opportunities:
Select your programme and preferred start date to begin your application.
We encourage you to apply at least one month prior to entry so that we have enough time to process your application. If you are also applying for funding or will require a visa then we strongly recommend you apply as early as possible. We may consider late applications if we have places available, but you should contact the relevant Admissions Office for advice first.
You must submit two references with your application.
You must also submit a CV.
Find out more about the application process for this programme on the Data Science website:
Find out more about the general application process for postgraduate programmes: