Research Fellow (Mixed Integer Programming)

Full-time Other-General

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.

• 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.

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