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Massachusetts Institute of Technology Postdoctoral Associate in Cambridge, Massachusetts

Postdoctoral Associate

  • Job Number: 20631

  • Functional Area: Research - Engineering

  • Department: Center for Transportation & Logistics

  • School Area: Engineering

  • Employment Type: Full-Time

  • Employment Category: Exempt

  • Visa Sponsorship Available: Yes

  • Schedule:

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    Job Description

POSTDOCTORAL ASSOCIATE, Center for Transportation & Logistics (CTL) ( -Supply Chain Management (SCM), to develop scholarly competence by assisting on research projects with CTL research staff and Supply Chain Management program (SCM) ( master’s degree students, supporting teaching activities, and conducting independent research under the supervision of CTL senior researchers. SCM is CTL’s degree-granting educational program. Will support graduate-level teaching activities, conduct research, and publish in leading journals in the field; serve as mentor and thesis/capstone project advisor; support SCM research staff with the development and scoping of sponsored projects with corporate partners; publish impactful research in leading academic and business-oriented journals in the field; support SCM events, academic orientations, and/or related activities; and perform other duties as requested.

Job Requirements

REQUIRED: Ph.D. in supply chain management, logistics, transportation, operations management, industrial engineering, operations research, computer science, information systems, business management, or related field; in-depth research knowledge and experience in at least one of the following--data-driven logistics/supply chain management, supply chain analytics, statistical analysis and probability, optimization, simulation, and/or machine learning/artificial intelligence; publication in academic journals in the field and/or pipeline of potential publications; proficiency with coding in programming languages, preferably Python; excellent communication and presentation skills; self-motivation; and an interest in research, teaching, and other academic activities. PREFERRED: in-depth knowledge of and relevant experience with applied projects on data analytics and machine learning in the context of logistics, supply chain, operations, and/or related field; teaching experience (e.g., support, TA, or leading lectures) in courses on logistics and supply chain management and/or quantitative-oriented courses (e.g., coding, statistics, and/or mathematical modeling); and work experience in the supply chain management, logistics, or freight transportation fields. Job #206311/7/22