Research Fellow in Mixed Integer Programming

Laplace Expert Ltd; Singapore; On-site; SGD 65,000 - 90,000; Full time

Job summary

The National University of Singapore invites applications for a Research Fellow in Mixed Integer Programming. The fellow will work under Dr Guanyi Wang to advance algorithms and theory for MILP, nonlinear optimization, and structured learning as part of a large-scale decision-making research program.

This postdoctoral role focuses on mathematical optimization, balancing rigorous analysis with numerical experiments to provide practical guarantees and scalable methods.

Qualifications

• PhD in optimization, OR or related field.
• Strong background in MILP, nonlinear optimization, or structured learning theory.
• Experience with mathematical modeling and numerical simulation.

Responsibilities

• Develop algorithms and theoretical guarantees for MILP, nonlinear optimization, and structured learning.
• Analyze non-convex optimization problems and large-scale decision-making models.
• Combine rigorous theory with numerical simulations to validate methods.

Skills

MILP

Nonlinear optimization

Structured learning

Education

PhD in Optimization/Operations Research

Job description

Research Fellow in Mixed Integer Programming

National University of Singapore

14 November 2026 listed by AcademicJobs; exact official cutoff time not independently verified.

About This Opportunity

NUS seeks a postdoctoral Research Fellow under Dr Guanyi Wang to develop algorithms and theoretical guarantees for mixed-integer linear or quadratic programming, non-convex optimization and structured learning.

The postdoc focuses on mathematical optimization for large-scale decision-making. The fellow will develop algorithms for mixed-integer linear and quadratic programming, analyse non-convex optimization problems and explore structured-learning methods, combining rigorous theory with numerical simulation.

Level Postdoc

Time Commitment Full-time

Reference Code 33719

Field Mixed-Integer Programming and Optimization

Specialization Statistics & Operational Research

Organization Type University

Requirements

• Education PhD in Optimization, Operations Research or related field.
• Experience Strong background in mixed-integer programming, nonlinear optimization and/or structured learning theory.
• Technical Skills Mixed-integer programming Nonlinear optimization Structured learning Numerical simulation