Research Fellow (1-year contract), LKCSB

COMPANY DESCRIPTION

Singapore Management University is a place where high-level professionalism blends together with a healthy informality. The 'family-like' atmosphere among the SMU community fosters a culture where employees work, plan, organise and play together - building a strong collegiality and morale within the university.

Our commitment to attract and retain talent is ongoing. We offer attractive benefits and welfare, competitive compensation packages, and generous professional development opportunities - all to meet the work-life needs of our staff. No wonder, then, that SMU continues to be given numerous awards and recognition for its human resource excellence.

RESPONSIBILITIES

• This position is for Lee Kong Chain School of Business (LKCSB).
• Develop analytical and computational models of electric vehicle business models.
• Develop learning algorithms to optimize the operations of such business models.
• Support the design and execution of a field pilot, including research protocols, participant recruitment, scheduling, monitoring, and data collection.
• Coordinate research activities with the Pl, project collaborators, participating drivers, site hosts, and technical partners.
• Develop and maintain reproducible code and research datasets; ensure data quality, confidentiality, and compliance with applicable research requirements.
• Conduct quantitative analyses and prepare journal manuscripts, conference presentations, progress reports, and grant deliverables.

• PhD in Operations Management, Operations Research, Industrial Engineering, Management Science, Computer Science, Data Science, Applied Mathematics, Economics, or a related quantitative discipline, completed by the appointment date.
• Demonstrated research experience in stochastic or dynamic optimization, online learning or sequential decision-making, matching models, or closely related areas.
• Experience in EVN2X, energy systems, sustainable operations, or analysis of pilot or field data is advantageous.
• Strong skills in mathematical modelling, stochastic optimization, dynamic programming, and online learning algorithms; familiarity with sequential decision-making, multi-armed bandits, Thompson sampling, spatial matching, machine learning, and statistical data analysis.
• Ability to formulate and analyse stochastic models, derive structural properties, and develop scalable algorithms; proficiency in at least one scientific programming language (e.g., Python, MATLAB, Mathematica, Julia, or R).
• Ability to maintain reproducible code and conduct rigorous numerical studies; strong academic writing, communication, and collaboration skills.

#LI-JN2