PhD in Statistics and Data Science
About This Programme
A University-funded (Year 1, pending a faculty advisor match) PhD in Statistics and Data Science: advanced statistical theory and learning research with a 32-credit thesis.
Course Highlights
- Ph.D. students are centrally funded by MBZUAI in Year 1 while matching with a faculty advisor, then funded by that advisor from Year 2, subject to a confirmed match and satisfactory progress.
- Advanced statistical theory, high-dimensional statistics and statistical learning.
- Access to computing labs with nearly 1,000 Nvidia DGZ-1/2 GPU servers.
- Qualifying and Candidacy exams then a 32-credit thesis.
What You'll Study
A 3–4 year full-time doctoral programme on the Masdar City campus with advanced statistics and data-science cores, electives, research methods and an internship, a Qualifying Exam (Year 1) and Candidacy Exam (Year 2), then an original 32-credit thesis. Ph.D. students are centrally funded by MBZUAI in Year 1 while matching with a faculty advisor, then move to that advisor's funding from Year 2, subject to a confirmed match and satisfactory progress.
Core courses
Core: 4 courses, 16 credit hours, taken by every student.
- Advanced Probability Theory and Stochastic Processes (SDS8101)4 credits
- Advanced Mathematical Statistics (SDS8102)4 credits
- Statistical Learning (SDS8103)4 credits
- Computation in the Era of Big Data (SDS8104)4 credits
Research methods, internship and thesis
- Advanced Research Methods (RES899)2 credits
- Ph.D. Internship (up to four months) (INT899)2 credits
- Statistics and Data Science Ph.D. Research Thesis (SDS899)32 credits
Elective courses
Students select a minimum of two elective courses totalling 8 credit hours.
Published elective list
- Advanced Topics in Continuous Optimization (ML804)4 credits
- Advanced Topics in Reinforcement Learning (ML806)4 credits
- Causality and Machine Learning (ML808)4 credits
- Dimensionality Reduction and Manifold Learning (ML813)4 credits
- Advanced Machine Learning (ML8102)2 credits
- Algorithms for Big Data (ML8501)2 credits
- Tiny Machine Learning (ML8505)2 credits
- Collaborative Learning (ML8509)4 credits
- Deep Learning Theory (SDS8501)4 credits
- Generative Models (SDS8502)4 credits
- High-dimensional Probability and Statistics (SDS8503)4 credits
Entry Requirements
Three references and an independent research statement. Screening exam and technical interview.
Careers
Graduates become statisticians, research scientists and faculty across academia, industry and government.
Accreditation & Professional Recognition
Accredited by the UAE Commission for Academic Accreditation (status Active on the CAA register).
Programme Details
Award
Doctor of Philosophy (PhD) in Statistics and Data Science
Start Date
Annual Fall intake (August)
Typical Offer
Bachelor's CGPA 3.5 or master's 3.0 (STEM); IELTS 6.5 / TOEFL 90
Duration
4 years
Qualification
Doctorate
Subject Area
Statistics & Data Science
Study Pattern
Full time
Delivery Format
In person