Mohamed bin Zayed University of Artificial Intelligence
Location
Abu Dhabi, UAE
Open Date
Sep 16, 2026
Description
Applications are invited for a fully funded two-year postdoctoral position in Statistics, Machine Learning, or a closely related field under the supervision of Prof. Souhaib Ben Taieb at MBZUAI in Abu Dhabi, UAE. The successful candidate will conduct research in modern statistics, machine learning, or related areas. Relevant topics may include, but are not limited to, probabilistic machine learning, decision-focused uncertainty quantification, conformal prediction, tabular foundation models, and time-series forecasting. Candidates with strong backgrounds in other areas of statistics and machine learning are also encouraged to apply. The lab collaborates with leading academic and industry partners. The position includes a competitive tax-free monthly salary, housing allowance, comprehensive medical insurance, an annual return flight to the home country, and full visa application support.
Key Responsibilities:
- Conduct original research in modern statistics, machine learning, artificial intelligence, or a related area.
- Develop and evaluate new statistical or machine-learning methods through appropriate theoretical analysis and empirical studies.
- Publish research papers in top-tier conferences and journals and present findings to technical and non-technical audiences.
- Collaborate with research-group members and academic and industry partners, and contribute to ongoing projects and shared research resources.
- Mentor and support graduate students and junior researchers, as needed.
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) is a world-leading university dedicated to advancing AI as a global force for good. The UAE’s visionary leaders established MBZUAI to educate and develop top talent, conduct advanced research, foster an innovation ecosystem, and act as a strategic think tank for the public and private sectors.
The University attracts world-class thinkers and doers in computer science, AI, bioscience, humanities and beyond. Our groundbreaking academic research initiatives are working on developing future solutions that will impact the world and change the way we imagine things.
Why Join MBZUAI?
- Top-Tier Compensation: Competitive salaries aligned with leading global academic institutions
- Exceptional Benefits:
- Comprehensive health & life insurance
- Relocation support for international hires
- Live in Abu Dhabi: World’s safest city, year-round sunshine, rich culture, and modern amenities
- Industry & Government Collaborations: Work with top AI researchers, leading tech firms, and policymakers
Qualifications
- PhD in Applied Mathematics, Computer Science, Statistics, Machine Learning, Data Science, or a closely related field.
- Strong research background in statistics, machine learning, artificial intelligence, data science, or a related area.
- Proficiency in programming (e.g. Python) and experience with commonly used machine-learning and AI tools.
- Strong publication record in leading conferences or journals.
- Excellent English communication skills, both oral and written, and the ability to work independently and collaboratively.
PREFERED QUALIFICATIONS
- Advanced training in an area relevant to modern statistics, machine learning, artificial intelligence, or data science.
- Experience developing reproducible research software or conducting large-scale computational experiments.
- Familiarity with modern machine-learning frameworks, scientific-computing tools, or AI-assisted research and development tools.
- Experience working in multidisciplinary or international research collaborations.
Application Instructions
To apply for this position, please submit the following items: Interested candidates should submit the following documents:
- Cover Letter
- Curriculum Vitae (C.V.)
- A link to your Google Scholar profile.
- A 1–2 page research statement outlining directions you would like to pursue in AI and weather forecasting.
- Name and contact details for three referees (Referees will be contacted if the candidate moves to the final stages)