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Postdoctoral Associate
  • Job Number: 25876
  • Functional Area: Research - Engineering
  • Department: Center for Transportation & Logistics
  • School Area: Engineering
  • Pay Range Minimum: $73,308
  • Pay Range Maximum: $90,000
  • Employment Type: Full-Time
  • Employment Category: Exempt
  • Visa Sponsorship Available: Yes
  • Schedule:
  • Pay Grade: No Grade


Posting Description

POSTDOCTORAL ASSOCIATE, Center for Transportation & Logistics (CTL) - Intelligent Logistics Systems (ILS) Lab, will conduct independent, publishable research; contribute to sponsored research projects with industry partners; develop innovative analytical and computational methods; publish findings in leading academic journals; mentor graduate students; support graduate-level teaching activities; participate in research group and academic program activities; and contribute to the continued growth of the ILS Lab and CTL's research mission. Additional responsibilities may be assigned as needed.

The ILS Lab develops innovative methods at the intersection of operations research, artificial intelligence, and machine learning to solve complex supply chain, logistics, and transportation challenges in collaboration with global industry partners.

The full job description is available, here: https://www.dropbox.com/scl/fi/7g4rlzhx85n9a9dwdf7ec/CTL-Postdoctoral-Associate.pdf?rlkey=3gyfzi607tn9x61yolbjst4ev&st=ug9fa910&dl=0

Job Requirements

REQUIRED: Ph.D. in Supply Chain Management, Logistics, Transportation, Operations Research, Industrial Engineering, Computer Science, Information Systems, Operations Management, or a closely related field; demonstrated research expertise in one or more of the following: optimization, simulation, data analytics, machine learning, artificial intelligence, or statistical analysis applied to logistics, transportation, or supply chain management; record of scholarly publications or a strong publication pipeline; proficiency in Python or comparable programming languages; strong written, verbal, and presentation skills; and ability to work both independently and collaboratively in a multidisciplinary research environment. PREFERRED: Experience applying machine learning or advanced analytics to real-world logistics or supply chain problems; experience mentoring graduate students; teaching or instructional experience at the university level; and industry or applied research experience in supply chain management, logistics, or freight transportation.

7/27/2026