Postdoctoral Associate, MIT Low Income Firms Transformation (LIFT)

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POSTDOCTORAL ASSOCIATE, Center for Transportation & Logistics (CTL) , to join the MIT Low Income Firms Transformation (LIFT) , a new research lab aimed at alleviating poverty and LIFTing the life of the bottom billion. Its approach is to contribute to the survival and growth of micro and small companies by improving their business and supply chain management capabilities.  Will assist with research projects and teaching activities and conduct independent research under the supervision of senior researchers.  Responsibilities include conducting empirical research with micro and small firms in Latin America, including data collection, field interventions, and data analysis; publishing impactful research in leading journals in the field of supply chain management, with emphasis on empirical research and data analytics; collaborating on the development and scoping of sponsoring projects with corporate partners; writing grants/research proposals; serving as mentor/advisor for SCM master’s program thesis/capstone projects; and 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 knowledge of and experience in at least one of the following--empirical research, data analytics, statistical analysis and probability, and machine learning/artificial intelligence; track record of publishing in peer-review 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 working on applied projects involving data analytics and machine learning in the context of small firms, supply chain, and/or related fields; experience teaching supply chain management and/or logistics and quantitative-oriented courses (e.g., coding, statistics, probability, and mathematical modeling).  Job #21682

8/8/22