Postdoctoral Research Associate in AI and Bayesian Machine Learning – Emirates Aviation University

Job Description

Emirates Aviation University (EAU) invites applications for a Post-doctoral Research Associate in AI and Bayesian Machine Learning for Sustainable Transport Systems within the Faculty of Mathematics and Data Science.

This Bayesian Machine Learning Postdoc supports the Dubai RDI-funded project “Mapping and Modelling the Sustainability of Dubai’s Transport System.” The successful candidate will contribute to cross-disciplinary research on sustainable urban transport through AI-driven, probabilistic, and uncertainty-aware modelling.

Employer: Emirates Aviation University
Faculty: Mathematics and Data Science
Location: Dubai, United Arab Emirates
Project: Mapping and Modelling the Sustainability of Dubai’s Transport System
Funding: Dubai RDI
Contract Duration: Fixed term – 2 years
Advertised Start Date: July 1, 2026
Application Review: Rolling basis

Bayesian Machine Learning Postdoc – Position Overview

The successful candidate will develop and apply AI-driven and uncertainty-aware modelling approaches to support sustainability and resilience analysis for urban transport systems.

The research will integrate transport, environmental, and climate-related datasets within a systems-based decision-support framework.

As a result, the role combines:

• Artificial Intelligence.
• Bayesian and probabilistic modelling.
• Machine learning.
• Data-driven analysis.
• Sustainable transport research.
• Urban systems modelling.
• Scenario analysis.
• Policy-focused decision support.

The work is intended to produce robust, policy-relevant evidence for transport planning and sustainability decisions.

Key Research Responsibilities

The Postdoctoral Research Associate will be expected to:

• Contribute to the development of AI- and data-driven models for urban transport systems.
• Support sustainability and resilience assessments.
• Develop uncertainty-aware modelling approaches.
• Assist with model calibration and validation.
• Conduct scenario analysis using large and heterogeneous datasets.
• Integrate transport, environmental, and climate-related data.
• Support systems-based decision-making frameworks.
• Collaborate with interdisciplinary research teams.
• Align modelling activities with real-world planning and policy requirements.
• Translate technical research findings into accessible insights for non-technical stakeholders.

The role therefore requires both strong quantitative expertise and the ability to connect advanced modelling with practical transport and policy questions.

AI, Bayesian Modelling and Data Analysis

A core element of this position is the development of analytical approaches that account for uncertainty in complex systems.

The successful candidate should be comfortable working with:

• Machine-learning models.
• Probabilistic modelling.
• Bayesian methods.
• Computational modelling.
• Large and complex datasets.
• Data-driven research methods.
• Model validation.
• Scenario-based analysis.

In addition, advanced programming ability will be essential for implementing and testing research models.

Qualifications

Applicants must hold a PhD in one of the following areas:

• Data Science.
• Statistics.
• Mathematics.
• Engineering.
• Computer Science.
• A closely related discipline.

Required Research and Technical Expertise

Candidates should demonstrate strong expertise in:

• Machine learning.
• Probabilistic modelling.
• Data-driven analysis.
• Computational modelling.

Applicants should also have:

• Advanced computational skills.
• Strong proficiency in Python programming.
• Experience working with complex datasets.
• Experience using computational modelling tools.
• Ability to work effectively in interdisciplinary research environments.
• Ability to contribute to applied research projects.

Because the project addresses sustainable transport systems, candidates should also be comfortable working across disciplinary boundaries involving data science, transport, environmental systems, and policy.

Sustainable Transport Research Context

The project, “Mapping and Modelling the Sustainability of Dubai’s Transport System,” focuses on understanding transport sustainability through integrated modelling.

The successful candidate will contribute to analytical approaches that combine:

• Transport-system data.
• Environmental data.
• Climate-related information.
• Sustainability indicators.
• Resilience considerations.
• Uncertainty-aware modelling.
• Scenario evaluation.

Consequently, the research will connect advanced data science with practical questions surrounding urban transport planning and sustainability.

Interdisciplinary Collaboration and Policy Impact

This postdoctoral role involves close collaboration with researchers from different disciplinary backgrounds.

The successful candidate will help ensure that modelling approaches remain relevant to practical planning and policy requirements.

An important part of the position will therefore involve translating technically complex results into clear findings for stakeholders who may not have specialist expertise in AI, statistics, or computational modelling.

Strong communication skills and an applied research mindset will support success in this area.

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How to Apply

Applicants should submit:

• An updated CV.
• A short cover letter.

Applications should be sent by email to:

recruitment@eau.ac.ae

Applications will be reviewed on a rolling basis.

Applicants should confirm the current status of the vacancy with Emirates Aviation University before applying, particularly because the advertised start date was July 1, 2026.