Research Associate (Resilience and Operations Research)

The Role:
We are seeking a Research Associate to undertake advanced research at the intersection of resilience and operations research. This position focuses on applying methodologies from decision optimization, big data analytics, risk control, and neural network generative models to enhance resilience in various systems and processes. The role involves both theoretical development and practical application, leading to contributions in top-tier international journals and real-world implementations.

Responsibilities:

• Develop and refine algorithms for decision optimization and risk control, utilizing big data and advanced computational techniques.
• Engage with neural network generative models to explore new ways of enhancing system resilience across various domains.
• Stay abreast of the latest developments in resilience research, operations research, and related technical fields.
• Formulate and execute research projects that utilize state-of-the-art operations research techniques to address real-world challenges in resilience.

Collaborate with external partners and industry stakeholders to apply research findings in practical settings.

• Solid mathematical foundation and analytical skill; preferably with a Bachelor's degree in Mathematics.
• Adequate understanding of engineering and operations research, holding Master's and PhD degrees or having educational experience in these fields, with a focus on decision science, risk analysis, or related areas of resilience research.
• Demonstrated track record of independent research and publications in relevant areas.
• Experience with decision optimization techniques, big data decision-making, and risk control methodologies.
• Familiarity with neural network generative models and their applications in enhancing resilience is highly desirable.
• Proficiency in at least one of the following programming languages: Python, Go, Java, C/C++.
• Excellent interpersonal communication and presentation skills, capable of working collaboratively with interdisciplinary teams.
• Ability to work comfortably on multiple projects in a dynamic environment.
• Capacity to work independently as well as collaboratively as part of a team.

Location: Kent Ridge Campus

Organization: College of Design and Engineering

Department : Industrial Systems Engineering and Management

Employee Referral Eligible: No

Job requisition ID : 28322