Research Fellow (Air Transportation / Transportation Engineering / Statistics / Data Science / Operations Research / Applied Mathematics / Economics)

ATMRI at NTU is seeking a Research Fellow to conduct applied research in airport and airspace capacity, demand management, delay, operational performance, and sustainable aviation. The role will develop statistical, mathematical, causal-inference, simulation, and machine-learning methods using large-scale flight trajectory and operational datasets. Research may cover airport surface congestion, runway-system capacity, terminal airspace performance, delay propagation, multi-airport systems, performance benchmarking, and the impacts of capacity interventions. The successful candidate will develop reproducible models and decision-support methods, contribute to project milestones and high-impact publications, and work closely with academic, industry, airport, and regulatory stakeholders.

Responsibilities:

• Conduct research on airport and airspace capacity, demand management, delay, congestion, and operational performance.

• Develop statistical, mathematical, econometric, causal-inference, simulation, and machine-learning models using large-scale aviation datasets.

• Analyse airport surface, runway, terminal airspace, and multi-airport system operations, including traffic-flow and delay-propagation mechanisms.

• Develop capacity-estimation, demand-forecasting, performance-benchmarking, and what-if assessment methods to support planning and operational decision-making.

• Investigate the operational, environmental, safety, and economic impacts of airport capacity interventions and sustainable aviation measures.

• Process, integrate, visualise, and validate flight trajectory, operational, weather, and other relevant transportation datasets.

• Translate research outcomes into practical tools, technical reports, stakeholder presentations, and recommendations for industry and regulatory partners.

• Support delivery of project milestones and contribute to high-quality journal and conference publications and research proposals.

• Collaborate with multidisciplinary academic, industry, airport, airline, and air navigation service provider stakeholders, and mentor students or junior researchers where appropriate.

Requirements:

• Ph.D. in Air Transportation, Transportation Engineering, Statistics, Data Science, Operations Research, Applied Mathematics, Economics, or a related field.

• Expertise in statistical or mathematical modelling, causal inference, econometrics, simulation, machine learning, or spatiotemporal analysis.

• Strong programming skills in Python and/or R; experience with STATA, MATLAB, or SQL is advantageous.

• Experience with aviation, airport, airspace, flight trajectory, or transportation datasets.

• Strong publication record and good technical writing and communication skills.

• Ability to work in multidisciplinary teams and engage external and international stakeholders.

We regret to inform that only shortlisted candidates will be notified.