Professional Doctorate Data Science

Program Overview

Overview

The Professional Doctorate in Data Science at Stirling combines research, academia, industry expertise, and practical application to enhance employability. It is the first industrial doctorate of its kind, supported by The Data Lab - Scotland’s Innovation Centre for Data and AI.

Key Facts

• Award: ProfD
• Start date: September 2025, January 2026
• Duration: Doctorate full-time: 36 months, Doctorate part-time: 48-72 months
• Mode of study: full time, part time
• Delivery: on campus

Entry Requirements

Academic Requirements

• Students 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 experience.
• Students with suitable research-oriented Masters degrees in numerate and computational disciplines 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

• View the entry requirements for your country.

English Language 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.

Course Details

Modules

• The module information below provides an example of the types of course modules you may study.
• The details listed are for the academic year that starts in September 2025. Modules and start dates are regularly reviewed and may be subject to change in future years.

Teaching

• 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.

Assessment

• Assessment of the taught component of the program follows the standard assessment of MSc modules and may consist 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).

Fees and Funding

Fees and Costs

• 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.
• Eligible students could receive a scholarship worth between £4,000-£7,000.

Cost of Living

• If you’re domiciled in the UK, you can typically apply to your relevant funding body for help with living costs.
• International (including EU) students won’t normally be able to claim living support through SAAS or other UK public funding bodies.

After You Graduate

• Data analyst and scientist roles are in the top 10 global jobs expected to grow fastest between 2023 and 2027 (World Economic Forum survey, 2023).
• The Professional Doctorate in Data Science opens many career paths in various sectors such as banking and finance, data-driven marketing, sport and fitness, health and medicine, engineering, data journalism, mapping and GIS, and new media.
• Graduates can find employment in roles such as Data Scientist, Data Analyst, Data Engineer, Business Analyst, Quantitative Model Risk Analyst, and Researcher.