IDSS Postdoctoral Associate
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.
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 firstname.lastname@example.org: 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.