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Massachusetts Institute of Technology Postdoctoral Associate in Cambridge, Massachusetts

Postdoctoral Associate

  • Job Number: 24622

  • 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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    Posting Description

POSTDOCTORAL ASSOCIATE, Center for Transportation & Logistics (CTL)-Supply Chain Management (SCM) (multiple openings), 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. 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 supply chain management, logistics, or freight transportation fields. Job #24622

11/22/2024

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