POSTDOCTORAL ASSOCIATE, Institute for Data, Systems, and Society (IDSS), to teach and develop content for one or more existing online courses, sustaining the course(s) across the semester. Responsibilities include learning/developing expertise in the latest in education research and cognitive science as it relates to the digital learning environment; keeping abreast of advances in digital learning tools for engineering and mathematics; developing innovative online courses (MOOCs) and digital learning tools that enhance student learning by blending online and face-to-face learning; assisting faculty with building MOOCs on the edX platform, developing residential classes/modules on MITx, recording and producing faculty videos, and contributing original education content; coordinating and supervising/moderating active MOOCs; evaluating the effectiveness of online courses and pedagogical approaches by performing quality control reviews; meeting with Office of Digital Learning staff and learning scientists to incorporate and advance education research through their work within the department; identifying and promoting best practices for online course development, helping strengthen offerings, and researching and developing innovative course content and tools; and other duties as assigned.
Job Requirements
REQUIRED: Ph.D. (expected or obtained) in statistics, computer science, data science, economics, mathematics, or related discipline; domain-specific knowledge of the course material to be taught–probability, statistics, data analysis, and machine learning; experience with residential or online teaching; familiarity with digital learning technology, including edX/MITx platforms; strong time-management and oral and written communication skills; experience in a project setting with firm deadlines; ability to interact with learners of diverse backgrounds and build a supportive community through online discussions; expertise in probability theory, statistics theory, practical issues in statistics, R programming or probability theory, machine learning, and Python programming. Job #18209
In addition to applying online via the MIT website with a cover letter and CV, please submit the following documents in pdf format to idss-mm-pda@mit.edu : two additional letters of support, at least one of which should be external to MIT; one page teaching statement on your teaching philosophy and experience with digital learning; and an optional short, 5-10 minute video of a teaching segment on a topic in the fundamentals of machine learning or statistics.
This is a one-year appointment beginning no later than September 1, 2020, with the possibility of renewal for a second year based upon satisfactory performance and availability of funding.