Introduction

SIA-NUS Digital Aviation Corp Lab at the National University of Singapore (NUS) leverages NUS’s world class deep technology and multi-disciplinary research expertise across Artificial Intelligence (AI), Machine Learning, Data Science, Operations Research and Analytics, Optimisation, Automation, Sleep Studies and Design.

 Expertise, infrastructure and relevant background work done at NUS’s Institute of Operations Research and Analytics (IORA), School of Business, School of Computing and Department of Industrial Systems Engineering & Management would be tapped on to add value to the proposed projects.

The Research Associate will provide critical research, administrative, and project management support to the Corp Lab in preparation for its next phase. The role focuses on assisting with proposal writing, data collection, coordination across stakeholders, and supporting ongoing and new research projects to ensure timely and successful project delivery.

Job Description

The SIA-NUS Corporate Laboratory is seeking a highly motivated and qualified Research Fellow/Associate to join our multi-disciplinary research team for Phase 2 of the Lab’s activities. The successful candidate will play a critical role in managing and contributing to research on network planning and optimisation in collaboration with Singapore Airlines. This position provides an exciting opportunity to work at the intersection of academia and industry, addressing real-world challenges in airline network design, scheduling, and operational efficiency.

Key Responsibilities

• Lead and Manage Research Projects:
  Oversee research activities related to airline network planning and optimisation, ensuring milestones and deliverables are met according to project timelines.
• Collaboration:
  Work closely with Singapore Airlines’ technical and operational teams to identify key challenges, define research questions, and translate research findings into actionable insights and solutions.
• Algorithm Development:
  Develop, implement, and validate advanced optimisation and machine learning models for problems such as fleet assignment, schedule planning, and disruption management.
• Data Analysis:
  Analyse large-scale operational and commercial datasets to extract insights, formulate models, and evaluate solutions.
• Reporting & Dissemination:
  Prepare regular progress reports, technical documentation, and research publications. Present findings to both academic and industry stakeholders.
• Mentoring:
  Supervise and mentor junior researchers, research assistants, or PhD/master’s students as required.

Qualifications

• PhD/Masters in Operations Research, Industrial Engineering, Computer Science, Applied Mathematics, or a related discipline.
• Strong background in optimisation, mathematical modelling, and/or machine learning.
• Experience with airline operations, transport/logistics planning, or similar large-scale network optimisation problems is highly desirable.
• Proficient in programming languages and tools (e.g., Python, C++, MATLAB, R, Gurobi, CPLEX).
• Demonstrated ability to work independently and in a team, with excellent organizational and communication skills.
• Proven track record of high-quality research publications

Application Instructions

Interested applicants should submit the following documents via [NUS Careers Portal/Email address/other application method as appropriate]:

• Cover letter detailing relevant experience and motivation
• Curriculum Vitae (CV)
• Contact information for at least two referees
• Representative publications (if available)

About Us

NUS, Singapore’s flagship university, and SIA, Singapore’s flagship carrier, jointly established a 5-year SIA-NUS Digital Aviation Corporate Laboratory (Corp Lab) to create and commercialise innovative technologies that could accelerate the digital transformation of Singapore’s aviation sector and redefine the air travel experience.

To emerge ahead in today’s digital transformation era, SIA and NUS will jointly target Revenue Management & Dynamic Pricing (for smart data-driven optimization), Transforming Competency and Skill Development (for intelligent and personalised pilot and cabin crew training), Employee Wellness (for data-driven and scientifically-backed improvements to workforce safety, performance and productivity), and Passenger Comfort, Sleep and Cabin Service (for next-generation product offerings and unparalleled customer service within the cabin).

More Information

Location: Kent Ridge Campus

Organization: Inst of Operations Research & Analytics

Department : Inst of Operations Research & Analytics

Employee Referral Eligible: No

Job requisition ID : 29207