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Professional Doctorate Data Science

The first industrial doctorate of its kind will equip you with interdisciplinary research and practical skills for a job in data science or data analytics.

Data Science

Key facts

  • Award PhD
  • Start date September
  • Duration Doctorate full-time: 36 months, Doctorate part-time: 72 months
  • Mode of study Campus based, Stand-alone modules

Our Professional Doctorate in Data Science is the first industrial doctorate of its kind, and is supported by The Data Lab.

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 data science or data analytics.

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.

  • Top reasons to study with us
  • Course objectives

    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 and scientific disciplines
    • Provide the opportunity to plan, undertake and prepare publication quality research
  • Flexible learning

    If you are interested in studying a module from this course, the Postgraduate Certificate or the Postgraduate Diploma then please email graduate.admissions@stir.ac.uk to discuss your course of study.

    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.

  • Academic 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.

  • 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 6.0 with 5.5 in each skill
    • Cambridge C1 Advanced (CAE) 169 overall with a minimum of 162 in each sub-skill
    • Cambridge C2 Proficiency (CPE) 180 overall with a minimum of 162 in each sub-skill
    • Pearson Test of English (Academic) 54 overall with a minimum of 51 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
    • Trinity ISE II Pass overall with a Pass in each sub-skill, ISE III Pass overall and in all sub-skills, ISE IV Pass overall and in all sub-skills

    Last updated: 5 December 2019

    For more information on ways that you can meet our English language requirements, including options to waive the requirement, please read our information on English language requirements.

  • Pre-sessional English language courses

    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.

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 modules listed below are those currently intended for delivery in the next academic intake of this course. These may be subject to change as the University regularly revises and refreshes the curriculum of our taught programmes.

Course Details

  • Fees and costs
    2020/21 fees
     Home/EU studentsOverseas students
    Full programme fee £16,850 £43,450
     

    If you need to extend your period of study, you may be liable for an additional fee.

    If you are not studying full-time, the fee for each year will be calculated based on the number of credits you enrol on each year. 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 of up to £25,700 from your regional body:

  • Scholarships and funding

    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.

  • Cost of living

    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.

    EU and overseas 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.

    Find out about the cost of living for students at Stirling

  • Payment options

    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

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.

e-Skills UK estimate that the number of Data Science jobs in the UK has risen by 41% from 2012–2013. By 2020 there will be 56,000 Data Science jobs in the UK alone with Data Science professionals earning on average 31% more than other IT professionals (source: SAS.com).

  • Employability skills

    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.

  • Companies we work with

    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.

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