Overview
Our Professional Doctorate in Data Science is the first industrial doctorate of its kind, and is supported by The Data Lab innovation centre.
We build on Stirling’s highly successful taught MSc Data Science to equip you with a range of cutting-edge, interdisciplinary research and practical skills and tools, that will lead to an academic or industry job in the area of Data Science, with possible applications to sectors such as life-sciences, finance, engineering, computing, healthcare, fintech or business.
In addition to enhancing students’ employability through work-based learning, the doctorate prepares you to undertake interdisciplinary Data Science research, jointly supervised by world-leading Stirling academics and Data Science industry experts.
The Professional Doctorate consists of a one-year taught programme, based on Stirling MSc programmes in Data Science, and a two-year research programme, to be conducted in collaboration with an industrial partner around industry-relevant research questions. Students could be employees of the industrial partner looking for further training and qualification, or have already established a (potential) collaboration with an industrial partner willing to support the project.
Each of our MSc in Data Science or in Fintech may offer the opportunity to establish a suitable collaboration with an industrial partner, and then grant access to the second year of the Professional Doctorate in Data Science on a research programme agreed with the industrial partner.
Specific projects and collaborations can be considered on a case-by-case basis. An (in principle) agreement with an identified partner company is necessary for the research component of the program.
This professional/industrial doctorate is designed to:
- Equip professionals with the required multi-disciplinary skills, and underlying theoretical, practical and transferable knowledge, to undertake practitioner-oriented, impact-led research in data science.
- Give sound training in relevant practical, investigative, analytical and generic skills required for research in the area of data science.
- Experience of data science challenges and applications in a wide range of areas, such as business, healthcare, life science, fintech and scientific disciplines.
- Provide the opportunity to plan, undertake and prepare publication quality research.
The research component of the Professional Doctorate in Data Science is a project of industrial interest to be carried out in collaboration with a company supporting the project.
If you’re interested in studying a module from this course, the Postgraduate Certificate or the Postgraduate Diploma then please email Graduate Admissions to discuss your course of study.
The Professional Doctorate can be attended both as a full time or part-time course. The taught component is organised around learning material provided online, contact teaching and tutorial hours, and an “open-door” approach allowing students a direct contact with lecturers, providing for great flexibility in the organisation of study. The research component consists of a research project whose development can be planned by agreement between the student, the company and the academic supervisor.
If you’re interested in studying a module from this course, the Postgraduate Certificate or the Postgraduate Diploma then please email Graduate Admissions to discuss your course of study.
Entry requirements
Students applying may have a variety of backgrounds including:
- numerate and computational degrees (computing, mathematics, physics, engineering)
- medical/clinical, business, marketing or economics background, plus some relevant work (industrial or commercial) experience
Students may also come from other science or engineering backgrounds, to gain applied research and analytical skills that are in high demand in the Scottish job market.
Students with suitable research-oriented Masters degrees in numerate and computational disciplines (computing, mathematics, physics, engineering), will be considered for direct entry to the second year of the Doctoral Training Component, on a case-by-case basis.
An established, in-principle or under-discussion agreement with an industrial partner interested in collaborating and supporting the research component of the programme should be in place.
International entry requirements
If English is not your first language you must have one of the following qualifications as evidence of your English language skills:
- IELTS Academic or UKVI 6.0 with a minimum of 5.5 in each sub-skill.
- Pearson Test of English (Academic) 60 overall with a minimum of 59 in each sub-skill.
- IBT TOEFL 78 overall with a minimum of 17 in listening, 18 in reading, 20 in speaking and 17 in writing.
See our information on English language requirements for more details on the language tests we accept and options to waive these requirements.
If you need to improve your English language skills before you enter this course, our partner INTO University of Stirling offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for entry to this degree.
Find out more about our pre-sessional English language courses.
Course details
You will undertake a number of taught modules to equip you with the skills required for data science research. These modules are taught through lectures, practicals and small group work and are assessed through a variety of course work and exams.
Compulsory modules:
- Mathematical Foundations (10 credits)
- Statistics for Data Science (10 credits)
- Representing and Manipulating Data (20 credits)
- Commercial and Scientific applications (20 credits)
- Relational and non-relational databases (20 credits)
- Data Analytics (20 credits)
- Cluster Computing (20 credits)
- Research Dissertation project (60 credits)
To prepare for the professional doctorate, an independent research project (60 credits) will include a systematic review of an appropriately challenging applied research topic/area, and development of a full Doctorate research proposal as outputs – assessed through an oral viva exam and research poster presentation.
Following the taught component, you will undertake a period of industry-led applied research (360 level 12 credits) by working with experienced academic and industrial supervisors, on original piece(s) of an applied research project. The project could either be a single long project or a portfolio of data-centric projects, depending on the industrial organization’s strategic priority needs. Outcomes will be presented in a doctoral dissertation assessment through a viva examination by internal and external examiners.
Modules
The module information below provides an example of the types of course module you may study. The details listed are for the academic year that starts in September 2024. Modules and start dates are regularly reviewed and may be subject to change in future years.
Course Details
The taught component of the Professional Doctorate spans across the first year and mutates the modules from the various MSc in Data Science, and includes an advanced dissertation project with an assessment of the state of the art and research plan for the next two years.
The research component consists of a period of industry-led applied research, carried out by working with experienced academic and industrial supervisors, on original piece(s) of an applied research project. The project could either be a single long project or a portfolio of data-centric projects, depending on the industrial organisation’s strategic priority needs. Outcomes will be presented in a doctoral dissertation.
Assessment of the taught component of the program follows the standard assessment of MSc modules and may consists of a variety of assessment strategies, including written assignments, exams, individual projects, collaborative and group work, lab work, presentations and reports and a dissertation project.
The doctoral dissertation will be assessed through a viva examination by an internal and an external examiner (as in a PhD viva).
Assessment will be tailored to students’ special needs, where appropriate.
Dr Andrea Bracciali
Fees and funding
University of Stirling alumni will automatically be awarded a fee waiver for the first year of Masters studies through our Stirling Alumni Scholarship.
Applicants from the UK or Republic of Ireland who hold a first-class honours degree or equivalent will automatically be awarded a £2,000 scholarship through our Postgraduate Merit Scholarship.
If you need to extend your period of study, you may be liable for additional fees.
If you are studying part time, the total course fee will be split over the years that you study. The total fee will remain the same and will be held at the rate set in your year of entry.
For more information on courses invoiced on an annual fee basis, please read our tuition fee policy.
Eligible students could receive a scholarship worth between £4,000-£7,000. See our range of generous scholarships for international postgraduate students.
If you need to extend your period of study, you may be liable for additional fees.
If you are studying part time, the total course fee will be split over the years that you study. The total fee will remain the same and will be held at the rate set in your year of entry.
For more information on courses invoiced on an annual fee basis, please read our tuition fee policy.
| UK and Republic of Ireland students | International (including EU) students | |
|---|---|---|
|
Full course fee |
£20,200 | £52,200 |
|
Full-time annual fee (charged years 1-3) |
£6,733 | £17,400 |
| UK and Republic of Ireland students | International (including EU) students | |
|---|---|---|
| Full course fee | £20,600 | £53,200 |
| Full-time annual fee (charged years 1-3) | £6,867 | £17,733 |
This fee is charged as an annual course fee. If you need to extend your period of study or repeat study, you will be liable for additional fees. Your fees will be held at the same level throughout your course.
For more information on courses invoiced on an annual fee basis, please read our tuition fee policy.
Doctoral loans
If you're domiciled in England or Wales you may be eligible to apply for a doctoral loan from your regional body:
- English students can apply for a loan of up to £28,673 from Student Finance England.
- Welsh students can apply for a loan of up to £28,395 from Student Finance Wales.
Funding
Eligible international students could receive a scholarship worth between £4,000-£7,000. See our range of generous scholarships for international postgraduate students.
University of Stirling alumni will automatically be awarded a fee waiver for the first year of Masters studies through our Stirling Alumni Scholarship.
Applicants from the UK or Republic of Ireland who hold a first-class honours degree or equivalent will automatically be awarded a £2,000 scholarship through our Postgraduate Merit Scholarship.
If you have the talent, ability and drive to study with us, we want to make sure you make the most of the opportunity – regardless of your financial circumstances.
Learn more about available funding opportunities or use our scholarship finder to explore our range of scholarships.
Additional costs
There are some instances where additional fees may apply. Depending on your chosen course, you may need to pay additional costs, for example for field trips. Learn more about additional fees.
If you’re domiciled in the UK, you can typically apply to your relevant funding body for help with living costs. This usually takes the form of student loans, grants or bursaries, and the amount awarded depends upon your personal circumstances and household income.
International (including EU) students won’t normally be able to claim living support through SAAS or other UK public funding bodies. You should contact the relevant authority in your country to find out if you’re eligible to receive support.
We aim to be as flexible as possible, and offer a wide range of payment methods - including the option to pay fees by instalments. Learn more about how to pay
After you graduate
Demand for people with data science skills is projected to grow rapidly in the coming years attracting high salaries.
Our Professional Doctorate in Data Science is run in partnership with industry and is designed to produce graduates with the skills that companies need.
The Doctorate programme, equivalent to an Engineering Doctorate (EngD), is aimed at a clear and distinct market of professionals seeking to enhance their employability opportunities through applied, impact-led research. You’ll learn to develop and validate innovative, data-driven and evidence-based approaches within your chosen career. The programme is geared towards enhancing both your applied, multi-disciplinary research and employability skills in data science.
The doctorate is open to any profession where data-driven and data-intensive research, and its informational derivatives, are central to the development of sustainable business and industry models, including decision-making, project and risk evaluation, policy and technology development. The doctorate research component is relevant to the student’s professional setting and career aspirations.
Stirling is a member of The Data Lab, which is an Innovation Centre with the aim of developing the data science talent and skills required by industry in Scotland. The Data Lab collaborates with the University of Stirling to help deliver the course, and provide funding and resources for students. You can find out more about the Data Lab from their web site.
We have also developed this professional doctorate in partnership with global and local companies who employ data scientists. HSBC have a development centre in Stirling and have provided some very interesting Data Science projects to our students. Amazon’s development centre in Scotland is close by in Edinburgh. The first year of the course features a long Industry-led research dissertation project, generally in partnership with a company or technology provider. This provides students with a showcase of their skills to take to employers or launch online.
We also have a programme of invited speakers from industry who give the students a chance to ask questions of people who are doing data science every day. Recent companies have included MongoDB, SkyScanner and HSBC.
