Postdoctoral Associate, Center for Transportation and Logistics - Supply Chain Management

Location
Massachusetts, United States
Posted
12 Jan 2021
End of advertisement period
12 Mar 2021
Ref
19084
Contract Type
Permanent
Hours
Full Time

Working at MIT offers opportunities, an environment, a culture – and benefits – that just aren’t found together anywhere else. If you’re curious, motivated, want to be part of a unique community, and help shape the future – then take a look at this opportunity.

POSTDOCTORAL ASSOCIATECenter for Transportation & Logistics (CTL)-Supply Chain Management (SCM), to assist with research projects, support teaching activities, and conduct independent research.  MIT SCM has been CTL’s degree-granting program since 1998. It is delivered in two formats--a ten-month residential (SCMr) option and a blended (SCMb) option allowing MITx MicroMasters credential holders to earn an MIT master’s degree by completing one term on campus. Will support research and teaching activities related to streamline machine learning and data analytics applied in logistics and supply chain management; support graduate-level teaching activities for both SCM programs; serve as mentor and thesis/capstone project advisor; support SCM research staff in the development and scoping of sponsoring projects with corporate partners; publish research in leading academic/business-oriented journals, with emphasis on machine learning and data analytics; assist with teaching activities, with emphasis on machine learning and data analytics; support for student management, events, orientations, and/or other activities; and perform other duties as needed. 

Job Requirements

REQUIRED: Ph.D. in supply chain management/logistics/transportation/operations management/industrial engineering/operations research/computer science/information system/business management/related field; in-depth research knowledge in and experience with at least one of the following--data-driven logistics/supply chain, supply chain analytics, statistical analysis and probability, and/or machine learning/artificial intelligence; publications in academic journals in the field and/or pipeline of potential publications; proficiency coding in programming languages, preferably Python; excellent communication and presentation skills; and self-motivation. 

PREFERRED:  in-depth knowledge of and relevant experience in applied projects on data analytics and machine learning in the context of logistics, supply chain, operations, and/or related field; and teaching experience in courses on logistics and supply chain management and/or any quantitative-oriented courses (e.g., coding, statistics, mathematical modeling).  Job #19084

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