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.