Postdoctoral Researcher in Statistics & Machine Learning | MBZUAI

Job Description

The Computing and Mathematical Sciences Division at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) invites applications for a fully funded two-year Postdoctoral Researcher position in Statistics, Machine Learning, or a closely related field.

The successful candidate will conduct research under the supervision of Prof. Souhaib Ben Taieb in modern statistics, machine learning, artificial intelligence, and related areas.

Research topics may include probabilistic machine learning, decision-focused uncertainty quantification, conformal prediction, tabular foundation models, and time-series forecasting. Candidates with strong research backgrounds in other areas of Statistics and Machine Learning are also encouraged to apply.

Employer: Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
Division: Computing and Mathematical Sciences
Location: Abu Dhabi, United Arab Emirates
Position: Postdoctoral Researcher – Statistics and Machine Learning
Appointment: Fully funded, two years
Supervisor: Prof. Souhaib Ben Taieb
Open Date: 16 September 2026

Statistics Machine Learning Postdoc – Position Overview

The successful candidate will conduct original research across modern Statistics, Machine Learning, Artificial Intelligence, Data Science, or closely related areas.

Potential research directions include:

• Probabilistic Machine Learning.
• Decision-Focused Uncertainty Quantification.
• Conformal Prediction.
• Tabular Foundation Models.
• Time-Series Forecasting.
• Modern Statistics.
• Machine Learning.
• Artificial Intelligence.
• Data Science.

The research group also collaborates with leading academic and industry partners.

Original Research

The Postdoctoral Researcher will:

• Conduct original research.
• Develop new statistical methods.
• Develop new machine-learning methods.
• Evaluate new methods theoretically.
• Conduct empirical studies.
• Contribute to research projects within the group.

The position offers scope for both theoretical and computational research.

Probabilistic Machine Learning

One of the highlighted research areas is probabilistic machine learning.

Research may involve statistical approaches to modelling:

• Uncertainty.
• Prediction.
• Probabilistic inference.
• Data-driven decision-making.

Uncertainty Quantification

The position also includes potential research in decision-focused uncertainty quantification.

This may involve developing methods that connect uncertainty estimation with downstream decisions and predictive systems.

Conformal Prediction

Applicants interested in conformal prediction are encouraged to contribute to research on statistically principled uncertainty and predictive inference.

Tabular Foundation Models

Research may also include:

• Foundation models for tabular data.
• Machine-learning methods for structured datasets.
• Large-scale predictive modelling.

Time-Series Forecasting

Another highlighted area is:

• Time-series forecasting.

Candidates with expertise in forecasting, probabilistic prediction, temporal modelling, or related methods may contribute to this research direction.

Theoretical and Empirical Evaluation

The successful candidate will develop and evaluate new methods through:

• Theoretical analysis.
• Empirical studies.
• Computational experiments.
• Reproducible research workflows.

Research Publications

The Postdoctoral Researcher will be expected to:

• Publish research papers in top-tier conferences.
• Publish in leading journals.
• Present research findings.
• Communicate findings to technical audiences.
• Communicate findings to non-technical audiences.

Academic and Industry Collaboration

The research group collaborates with academic and industry partners.

The successful candidate will:

• Work with research-group members.
• Collaborate with academic partners.
• Collaborate with industry partners.
• Contribute to ongoing projects.
• Support shared research resources.

Graduate Student Mentoring

The position may include:

• Mentoring graduate students.
• Supporting junior researchers.
• Contributing to the development of the wider research group.

Required Qualification

Applicants must hold a:

• PhD in Applied Mathematics, Computer Science, Statistics, Machine Learning, Data Science, or a closely related field.

Research Background

Candidates should have a strong research background in one or more areas such as:

• Statistics.
• Machine Learning.
• Artificial Intelligence.
• Data Science.
• Related quantitative fields.

Programming Skills

Applicants should demonstrate:

• Proficiency in programming, including languages such as Python.
• Experience with commonly used Machine Learning and AI tools.

Publication Record

Candidates should demonstrate:

• A strong publication record in leading conferences or journals.

Communication and Collaboration

Applicants should have:

• Excellent oral English communication skills.
• Excellent written English communication skills.
• Ability to work independently.
• Ability to work collaboratively.

Preferred Qualifications

Preferred qualifications include:

• Advanced training relevant to modern Statistics.
• Advanced training in Machine Learning.
• Advanced training in Artificial Intelligence.
• Advanced training in Data Science.
• Experience developing reproducible research software.
• Experience conducting large-scale computational experiments.
• Familiarity with modern Machine Learning frameworks.
• Familiarity with scientific-computing tools.
• Familiarity with AI-assisted research and development tools.
• Experience in multidisciplinary research collaborations.
• Experience in international research collaborations.

Research Software and Computational Experiments

Experience in the following areas is preferred:

• Reproducible research software.
• Large-scale computation.
• Scientific computing.
• Modern Machine Learning frameworks.
• AI-assisted research tools.

Why Join MBZUAI?

MBZUAI offers a research environment focused on advancing Artificial Intelligence through research, education, innovation, and collaboration.

The position includes:

• Competitive tax-free monthly salary.
• Housing allowance.
• Comprehensive medical insurance.
• Annual return flight to the home country.
• Full visa application support.

Research Environment

Postdoctoral researchers at MBZUAI can work within an international research environment with opportunities for:

• Academic collaboration.
• Industry collaboration.
• Advanced AI research.
• Interdisciplinary projects.
• Professional development.

Recommended Professional Development

🎓 Recommended Course: Bayesian Statistics Specialization

The Bayesian Statistics Specialization from the University of California, Santa Cruz is closely aligned with the statistical foundations underlying probabilistic machine learning, uncertainty quantification, predictive modelling, and modern statistical inference.

It may be particularly relevant to postdoctoral researchers, statisticians, machine-learning researchers, data scientists, and doctoral candidates working on probabilistic or uncertainty-aware AI methods.

👉 Explore the Bayesian Statistics Specialization on Coursera

Affiliate disclosure: Arab Academic Jobs may receive a commission if you enroll through this link, at no additional cost to you.

Application Requirements

Interested candidates should submit:

• Cover Letter.
• Curriculum Vitae (CV).
• Link to Google Scholar profile.
• A 1–2 page research statement outlining directions the candidate would like to pursue in AI and weather forecasting.
• Names and contact details for three referees.

Referees will be contacted if the candidate progresses to the final stages of the recruitment process.

Job Summary

Employer	Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
Division	Computing and Mathematical Sciences
Location	Abu Dhabi, UAE
Position	Postdoctoral Researcher – Statistics and Machine Learning
Appointment	Fully funded, two years
Supervisor	Prof. Souhaib Ben Taieb
Open Date	16 September 2026
Required Qualification	PhD in Applied Mathematics, Computer Science, Statistics, Machine Learning, Data Science, or closely related field
Research Areas	Probabilistic ML, uncertainty quantification, conformal prediction, tabular foundation models, time-series forecasting
Programming	Python and commonly used Machine Learning / AI tools
Publication Requirement	Strong publication record in leading conferences or journals
Preferred Experience	Reproducible software, large-scale experiments, modern ML frameworks, scientific computing, AI-assisted R&D
Benefits	Tax-free monthly salary, housing allowance, medical insurance, annual return flight, visa support
Application Materials	Cover letter, CV, Google Scholar profile, 1–2 page research statement, three referees
Application Deadline	Not stated