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Doctor of Philosophy in Data Science


The PhD programme in Data Science is designed to equip professionals with an extensive understanding of data science principles, methodologies, and applications. In an era marked by rapid growth of data across various domains, this programme focuses on advancing knowledge in data-driven decision-making, predictive modelling, machine learning, and artificial intelligence. With an emphasis on rigorous research, the programme instils advanced knowledge grounded in mathematics, enabling students to contribute to industry innovation and acquire leadership roles within the field. The PhD programme provides students with a solid foundation in subject-specific knowledge and offers training for doctoral researchers through a variety of modules and research workshops. A supervisory team comprising experienced researchers offers diverse perspectives and expertise to support students, complemented by a community of peers and learning hub facilities provided at Emirates Aviation University (EAU).

Programme key features:

  • Comprehensive researcher development training.
  • Robust support system provided by trained PhD supervisors.
  • Cumulative submission of thesis components over time.
  • Opportunity to publish research.

Why enrol on this programme?

EAU provides exceptional education and research opportunities in Data Science, preparing students for success in data-driven decision-making, predictive modelling, machine learning, and artificial intelligence. The university offers an experienced faculty, a multinational student body, and a purpose-built campus in the heart of Dubai, ensuring a vibrant learning environment.

PhD students in Data Science will collaborate with distinguished faculty proficient in big data, data science, artificial intelligence, mathematics, and statistics, bringing expertise from top academic institutions and industries worldwide. EAU's faculty commitment to research, in collaboration with academic institutions, government organizations, and industry, provides an ideal environment for candidates to acquire cutting-edge knowledge and develop their research interests.

Candidates will receive excellent supervision and access to a full range of research workshops and resources, supporting their development as postgraduate researchers.


The PhD in Data Science is accredited by the Ministry of Education – Higher Education Affairs, UAE.

Career Prospects

Completion of the PhD in Data Science programme offers diverse career opportunities for professionals. Equipped with advanced skills and qualifications, graduates will contribute across academia, industry research, government agencies, and technology companies. With expertise in data-driven decision-making, predictive modelling, and machine learning, graduates will drive innovation across a spectrum of fields, including finance, healthcare, marketing, telecommunications, transportation, energy, education, and government policy.

Duration and Delivery:

Duration Mode of Delivery
Full-Time: Four years Face to face

The PhD consists of 540 credits, distributed as below:

Module Type Module Code Module Title Credits (CATS)

Research Methods Module

EAP01RE Research Methods 40

Subject Specific Modules








Machine Learning

Probability and Statistics for Data Science

Numerical Methods

Asymptotic Expansions and Perturbation Methods

Modelling with Partial Differential Equations

Big Data Analytics

Choose One Elective 







Elective Modules




Data-Driven Modelling of Dynamical Systems

Fourier Series

Techniques in Optimization





EAP01DI Doctoral Internship [3 months] 0



Total Credits 


On successful completion of the programme, a Postgraduate Researcher should be able to demonstrate knowledge and understanding, cognitive, practical and transferable skills, as outlined below:

Knowledge and Understanding

  • KU1 -Make a significant and original contribution to a specialised field of enquiry worthy of publication.
  • KU2 -Command highly specialised and advanced technical, professional and/or research skills including recognised theories, processes, analytical methods and uses of empirical evidence related to research.
  • KU3 -Propose, discuss, critically evaluate and defend such knowledge and scholarship with peers and explain the function and contexts in which specialist and advanced level research occurs.
  • KU4 -Debate the philosophy and research methodology, including design and management of projects and ethics, of research.

Cognitive (thinking) Skills

  • CS1 - Create and interpret new knowledge which is at the forefront of an academic discipline or an area of professional practice.
  • CS2 - Identify relevant research theories, methods or techniques, to undertake a large independent research project and critically evaluate the outcome
  • CS3 - Analyse and draw reasoned conclusions concerning structured and unstructured problems from documentation, practical activity, case studies, observations and sets of data.
  • CS4 - Synthesise ideas, theories or arguments and formulate research questions and research design.

Practical Skills

  • PS1 - Reflect, investigate, and apply knowledge which supports the research and programme of study.
  • PS2 - Apply and develop appropriate techniques and methodologies applicable to research and advanced scholarship.
  • PS3 - Communicate and work effectively to persuade and influence others.

Transferable Skills

  • TS1 -Written and oral communication and defence of ideas and arguments.
  • TS2 -Interpersonal skills including teamwork and problem-solving.
  • TS3 -Management and leadership skills including time management and project management conflict resolution.
  • TS4 -The ability to work independently dealing with complex and unpredictable situations in professional or equivalent environments.
  • TS5 -Research and analytical skills, including numerical and statistical skills where appropriate to manipulate and present data.
  • TS6 – The ability to select, justify and apply appropriate research and decision-making techniques relevant to the research and programme of study.
Minimum Admission Requirements Proficiency Requirements
  • A recognised Master’s degree in a discipline appropriate to the doctoral programme with a minimum CGPA of 3.0 out of a 4.0 scale.
  • The Master’s degree should be in computer science, engineering, mathematics, statistics, or a closely related discipline.
  • Applicants with a degree obtained outside the UAE must submit an equivalency of their degree issued by the Ministry of Education in the UAE.

The following minimum test scores are acceptable for non-native speakers:

  • EmSAT score of (1400)
  • TOEFL score of 550 (213 CBT, 79 iBT)
  • IELTS academic score of (6.0)

or their equivalents on other standardized national or internationally recognized tests approved by the Ministry of Education in the UAE

You will need to submit the following documents to

  • Research proposal (maximum of 3,000 words or 6 pages). The research area must be suitable for supervision by EAU faculty.
  • A letter of interest. 
  • Master's qualifications and transcripts in English.
  • Proof of English language proficiency (if applicable).
  • A Curriculum Vitae (cv)
  • Two supporting references are to be submitted by the referees, with at least one being academic.

Admission Interview

  • After the initial application review, candidates will be interviewed to assess their suitability and academic potential.
Mode of Study Registration Fee* Tuition Fees (AED)**
Full-Time AED 2,625 76,125 per year 


**Tuition Fees inclusive of VAT 5%