Digital Learning Postdoctoral Associate



Job description

Cambridge, MA

Job Number: 17616

Functional Area: Research – Engineering

Department: Center for Transportation & Logistics

School Area: Engineering

Employment Type: Full-Time

Employment Category: Exempt

Visa Sponsorship Available: Yes

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.

DIGITAL LEARNING POSTDOCTORAL ASSOCIATECenter for Transportation & Logistics (CTL), to conduct research in the area of digital learning. Will apply descriptive analytics techniques to better understand learner’s behavior in a MOOC-based program; apply machine learning techniques to categorize learners and build predictive models; implement experiments in a MOOC-based program and evaluate their impact; perform data analysis and data analytics; extract, clean, and refine relevant data from BigQuery; analyze click stream data, survey data, and other sources of data; assist in the development, implementation, and evaluation of new digital tools and assessments; and assist in running MOOCs in supply chain management, which may involve developing course content, managing communication with learners, analyzing course data, and proposing course improvements.

Job Requirements

REQUIRED: a Ph.D. degree in data science, computer science, learning analytics, learning sciences, operations research, information systems, engineering, or a related discipline that includes domain-specific knowledge in data analytics, statistics, and educational data mining; teaching experience in higher education settings in STEM fields and proficiency evaluating the effectiveness of learning materials.; strong problem-solving skills; working knowledge of or familiarity with statistical software and analytics tools to analyze big data sets; track-record of working both independently and collaboratively; must be organized, able to support multiple projects simultaneously, work effectively in a fast-paced, rapidly changing work environment; and good communication skills and ability to build strong working relationships with teammates, faculty, and staff. Supply chain management knowledge would be a plus.

Job #17616

How to apply

Apply online

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