Summary
United Arab Emirates University invites a Postdoctoral Fellow to join the Emirates Center for Mobility Research and work on an AI-enabled digital twin for sustainable urban mobility. The role involves research in multimodal data fusion, graph modelling, spatio-temporal learning, forecasting, and optimisation, as well as developing and validating a prototype and analytics dashboard. Applicants need a PhD in a relevant quantitative discipline, research experience in machine learning or deep learning, strong Python skills, and a record of peer-reviewed publications. The stated salary is AED 17,500; the posting does not specify a pay period or work location.
The posting
As published on uaeu.ac.ae. Pulled from the employer's site and shown as they wrote it.
Job description
United Arab Emirates University (UAEU) invites applications for a highly motivated Postdoctoral Fellow to join the Emirates Center for Mobility Research (ECMR) and contribute to the project “Smart Climate-Adaptive Mobility Digital Twin for Sustainable, Safe, and Inclusive Urban Mobility.” The project will develop and validate a real-time AI-enabled digital twin that integrates traffic, public-transport, parking, incident, weather, environmental, accessibility, pedestrian-exposure, and electric-vehicle charging data within one urban mobility intelligence framework.
The successful candidate will lead advanced research in multimodal data fusion, dynamic graph modelling, climate-aware spatio-temporal learning, federated intelligence, uncertainty quantification, explainable AI, and multi-objective optimisation. The platform will forecast mobility and climate-related risks, support simulation of adaptive interventions, and deliver a validated prototype, analytics dashboard, scholarly outputs, and potential intellectual property.
Minimum qualification
- A PhD in Computer Science, Artificial Intelligence, Data Science, Computer Engineering, Electrical Engineering, Software Engineering, Civil or Transportation Engineering, or a closely related quantitative discipline from an accredited university.
- Demonstrated research experience in machine learning or deep learning, including spatio-temporal modelling, graph learning, sequence modelling, multimodal learning, time-series forecasting, or intelligent decision systems.
- Strong Python programming skills and hands-on experience with deep-learning frameworks such as PyTorch or TensorFlow.
- Experience analysing and managing large, heterogeneous, time-series, spatial, geospatial, sensor, or mobility datasets.
- A strong record of peer-reviewed research publications and the ability to prepare high-quality scientific manuscripts and technical reports.
- Excellent written and spoken English, strong analytical and organisational skills, and the ability to work independently and within a multidisciplinary team while meeting project milestones.
Preferred qualification
- 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 transformer models, 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 systems.
- Familiarity with GIS, climate or weather data, environmental monitoring, EV-charging systems, accessibility analysis, or hot-climate urban operations.
- Evidence of 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.
- Strong project-management, communication, presentation, documentation, version-control, and interpersonal skills.
- Ability to translate complex technical results into actionable information for researchers, planners, operators, and policy stakeholders.
- Ability to mentor junior researchers and contribute positively to a collaborative, multidisciplinary research culture.
Salary range
17500 AED
Department
Emirates Cntr. for Mobility Reserch
College or division
Research Centers