Research Fellow (Mixed Integer Programming)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Mixed-Integer-Programming%29/33719-en_GB/

We regret that only shortlisted candidates will be notified.

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.