Information on MIT's COVID-19 vaccination requirement can be found at the bottom of this posting.

DIGITAL LEARNING LAB FELLOW, ARTIFICIAL INTELLIGENCE AND DECISION MAKING (AI+DM), Electrical Engineering and Computer Science (EECS), to oversee and lead the running of one or more of the AI+DM courses that comprise the MicroMasters program. Responsibilities include contributing to the development, revamping, and management of AI+DM MicroMasters courses (which span probability, statistical data analysis, machine learning, optimization, game theory, and computer vision), managing course materials and related content; designing, building, and optimizing learner assessment tools (e.g., problem sets and exams); overseeing and managing live courses, including key aspects of learner communication, performance tracking, and online exam administration; leading teaching assistants and community teaching assistants in facilitating instructive, productive discussions in live course forums; organizing and running online webinars and planning and managing live exams using online proctoring technology; and conducting data analysis, proposing course improvements, and supporting other educational and research activities.

Job Requirements

REQUIRED: master's degree in engineering/related field; at least one year of relevant experience in online or higher education; excellent organizational and management skills; and excellent communication skills for conducting live webinars. Must be able to manage multiple priorities and deliver high-quality results on deadline; adapt to a rapidly changing platform/environment; work independently; and build strong collaborative relationships with teammates/faculty/staff. PREFERRED: Ph.D. in computer science, statistics, or related field; proficiency evaluating the effectiveness of learning materials and academic assessment; strong problem-solving/debugging skills; working knowledge of/familiarity with statistical software and analytics tools for analyzing big data sets; working knowledge of Python; proficiency with BigQuery and web-based tools; experience with HTML and LaTeX; and interest in educational technology, digital teaching and learning in higher education, producing educational content, academic assessment methodologies, and delivering and managing online educational programs. Job #21568

In addition to applying via the MIT website, all applicants are asked to register with and submit application material to the EECS search website at https://faculty-searches.mit.edu/eecs_lect2/. Application material should include a cover letter speaking to qualifications and preferred course assignments; a teaching statement specifying teaching beliefs and practices; a CV listing educational background, publications, talks, and other applicable experience; and two letters of recommendation from previous teaching experience(s). The MIT application only allows for submission of a cover letter and resume/CV. As a result, the teaching statement, CV, and letters need to be submitted as a single pdf as part of the resume field.

7/25/22