Job Description
This postdoc will work under the supervision of Dr. Guanyi Wang in ISEM at NUS to explore cutting-edge algorithms, derive rigorous theoretical guarantees, and implement numerical simulations.
The postdoc will engage in research including, but not limited to, the following areas:
- Mixed-Integer Linear / Quadratic Programming for large-scale decision-making problem
- Non-Convex Optimization and theoretical analysis
- Structured Learning & Learning Applications
Job Requirements
A qualified candidate should satisfy the following requirements:
- A Ph.D. degree in Optimization, Operations Research or related fields
- A solid research background in Mixed-Integer Programming, Nonlinear Optimization, and/or Structured Learning Theory.
- A strong publication record in top-tier optimization journals is preferred.