The Institute of Operations Research and Analytics (IORA) at National University of Singapore (NUS) is seeking a dedicated and analytical Research Fellow our team. The selected candidate will engage in cutting-edge research with our industry partner, focused on optimizing the liner shipping service network, which is pivotal to global trade. This involves enhancing the efficiency of operational maritime lines through strategic modifications, addressing challenges such as line configurations, port schedules, and operational costs.
Key Responsibilities
Conduct extensive research to understand and improve the complex systems of liner shipping service networks, with a particular focus on service network structure, scheduling, and fleet management.
Utilize machine learning techniques, particularly supervised learning and reinforcement learning, to predict maritime service demand and optimize line designs.
Implement the Monte Carlo Tree Search (MCTS) methodology to explore and evaluate optimal line configurations, contributing to the dynamic and cost-effective operation of maritime networks.
Collaborate with a team to develop and refine methodologies, and translate findings into actionable optimization strategies for immediate and incremental improvements.
Produce scholarly articles for journal publication, present findings at relevant conferences, and develop educational materials based on the research.
Qualifications
PhD in Operations Research, Transportation Engineering, Industrial Engineering, or related fields.
Experience in maritime industry research, particularly in liner shipping service network optimization.
Strong background in machine learning, especially in supervised learning and reinforcement learning.
Excellent analytical, problem-solving, and computational skills.
Ability to work collaboratively in a multidisciplinary team and communicate complex ideas effectively.
Track record of scholarly publications in related fields is an advantage.
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