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Job Description

The Department of Industrial Systems Engineering and Management is looking for self-motivated postdoctoral researcher with a Ph.D. degree in Mathematics, Operations Research, Computer Science or related fields.

The postdoctoral researcher will be involved in applying cutting-edge Large Language Model (LLM) based methodologies to design novel mixed-integer programming (MIP) algorithms, deriving theoretical results, and implementing numerical simulations under the joint supervision of Dr. Guanyi Wang and Dr. Hanzhang Qin.

In particular, research directions include, but not limited to, the following aspects:

• Reformulation & Relaxation. Approaches to generate efficient/effective reformulations and relaxations for (large-scale) decision-making problems under uncertainty, with a specific focus on LLM based methodologies.

• Computation. Learning based preconditioning, heuristic, branching, and column/row generation methods for computationally hard Combinatorics Optimization (CO) problems.

• Learning with Structures. Approximation algorithms for learning with geometric structures (e.g. structured sparsity) in high dimensions, and their applications in combinatorics, signal process, and data analytics.

Job Requirements

Potential applicants should satisfy the following requirements:

• A Ph.D. degree in Mathematics, Operations Research, Computer Science or related fields.

• Solid research backgrounds in deep learning, with applications in MIP, CO or related fields.