Research - Laboratory/Non-Laboratory, Staff/Administrative
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.
RESEARCH SCIENTIST , Center for Transportation & Logistics (CTL)-Supply Chain Management program (SCM) , to support the SCM program, work with corporate partners in conducting research, and teach. SCM is CTL's degree-granting educational program. SCM attracts a diverse group of students from across the globe and combines analytical, engineering-focused coursework with advanced leadership skills. It is currently delivered in two formats--a ten-month residential (SCMr) option and a blended (SCMb) option. Will lead the streamline on machine learning and data analytics applied in logistics and supply chain management. This involves creating, supporting, and disseminating new knowledge in the field and graduate-level teaching activities for both programs. This includes acting as lead instructor of Database Analysis for Supply Chain Management (Fall), Applied Programming and Data Analysis in Python (IAP-pre-Spring), and Data Science and Machine Learning for Supply Chain Management (Spring). Will also lead Python/machine learning workshops; advise thesis/capstone projects; participate in academic and practitioner-oriented conferences/symposia/meetings; publish research-oriented papers in peer-refereed scholarly journals/academic proceedings/trade journals/CTL working papers; and participate in corporate outreach programs.
Job Requirements REQUIRED : Ph.D. in supply chain management, logistics, transportation, operations management, computer science, information systems, general management, or related field; experience in and in-depth knowledge of at least one of the following--supply chain analytics, machine learning/artificial intelligence, statistical analysis, and probability; publications in academic journals in the field and pipeline of potential publications; coding proficiency in multiple languages, preferably Python; ability to teach difficult quantitative courses, e.g., coding, statistics, and mathematical modeling; grounding in academia, but with ability to work with industry and government agencies; experience working without hands-on guidance/direction; willingness to contribute to CTL's broader mission; and excellent communication and presentation skills. Job #19442
Internal Number: 19442
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