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Lecturer - Digital Learning Lab Fellow - AI+DM

Electrical Engineering and Computer Science

The position oversees and leads the running of one or more of the Artificial Intelligence and Decision-Making (AI+DM) courses that comprise the MicroMasters program.   Responsibilities include: contributing to the development, revamping and management of courses that comprise the MicroMasters Program in AI+DM (these courses 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 such as 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 to facilitate instructive and productive discussions in live course forums; organizing and running online webinars connected to MicroMasters contents and planning and managing live exams using online proctoring technology.   Conducting data analysis, propose course improvements, and support other educational and research activities as part of the MicroMasters team.   We are looking for candidates who share our passion for advancing knowledge through massive, open, and online education.   Involves working closely with MIT staff, researchers and faculty.

Job Requirements:

REQUIRED: Master's degree in engineering or related field with proven ability and flexibility to adapt to a rapidly changing platform/environment; and an ability to deliver high quality results while managing multiple priorities.   The successful candidate will possess excellent organizational and management skills; track-record of working both independently and collaboratively; deadline-oriented attitude; attention to detail; Excellent communication skills to conduct live webinars and the ability to build strong working relationships with teammates, faculty, and staff.

PREFERRED: PhD in Computer Science, Statistics, or related field.   Proficiency evaluating the effectiveness of learning materials and academic assessment.   Strong problem-solving / debugging skills and working knowledge or familiarity with statistical software and analytics tools to analyze big data sets.   A demonstrated working knowledge of Python.   Proficiency in BigQuery, and Web-based tools.   Experience with HTML and LaTeX.   Minimum one year of relevant experience in online or higher education.   An interest in educational technology, digital teaching and learning in higher education, production of educational content, academic assessment methodologies, and the delivery and management of online educational programs.

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/register.tcl .   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).   Complete applications should be received by November 1, 2023. Applications will considered until position is filled.

MIT is an equal employment opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, sex, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, ancestry, or national or ethnic origin. MIT's full policy on Nondiscrimination can be found at the following: https://policies.mit.edu/policies-procedures/90-relations-and-responsibilities-within-mit-community/92-nondiscrimination .

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