Postdoctoral Fellow

Role and project

Research and delivery

• Lead research in multimodal data fusion, dynamic graph modelling, climate-aware spatio-temporal learning, federated intelligence, uncertainty quantification, explainable AI, and multi-objective optimisation.
• Integrate traffic, public transport, parking, incidents, weather, environmental, accessibility, pedestrian-exposure, and EV-charging data.
• Support risk forecasting and simulation of adaptive interventions; deliver a validated prototype and analytics dashboard.
• Plan research, evaluate and benchmark results, maintain reproducibility, prepare scholarly outputs, and translate findings for stakeholders.
• Mentor junior researchers and contribute to a multidisciplinary research culture.

Minimum qualifications

• PhD in a listed quantitative discipline, including computer science, AI, data science, computer, electrical or software engineering, civil or transportation engineering, or a closely related field.
• Demonstrated machine-learning or deep-learning research experience, including a relevant modelling or intelligent decision-systems area.
• Strong Python programming and hands-on experience with PyTorch or TensorFlow.
• Experience analysing and managing large, heterogeneous time-series, spatial, geospatial, sensor, or mobility datasets.
• Strong peer-reviewed publication record and ability to prepare scientific manuscripts and technical reports.
• Excellent written and spoken English; strong analytical and organisational skills; ability to work independently and in a multidisciplinary team and meet milestones.

Preferred qualifications

• Experience in digital twins, intelligent transportation systems, smart-city mobility, traffic safety, transportation analytics, or connected and autonomous mobility.
• Experience with graph neural networks, temporal attention or transformers, multi-task learning, federated learning, explainable AI, privacy-preserving analytics, or uncertainty-aware prediction.
• Knowledge of multi-objective optimisation, reinforcement learning, control, simulation-based decision support, or operations research.
• Experience with IoT or sensor integration, edge/cloud computing, real-time data pipelines, dashboards, or deployment-oriented AI.
• Familiarity with GIS, climate or weather data, environmental monitoring, EV-charging systems, accessibility analysis, or hot-climate urban operations.
• Interdisciplinary or international collaboration, funded-project experience, stakeholder engagement, patents, software prototypes, or research commercialisation.

Expected skills

• Advanced research design, critical analysis, experimental planning, benchmarking, quantitative evaluation, and scientific reproducibility.
• Project-management, communication, presentation, documentation, version-control, and interpersonal skills.
• Ability to explain complex technical results to researchers, planners, operators, and policy stakeholders.
• Ability to mentor junior researchers and contribute to a collaborative research culture.

Salary

• The description lists a salary range of 17,500 AED but does not state a pay cadence.