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Lecturer and Digital Learning Lead
  • Job Number: 21568
  • Functional Area: Academic (non-faculty)
  • Department: Electrical Engineering & Computer Science
  • School Area: Engineering
  • Employment Type: Full-Time
  • Employment Category: Exempt
  • Visa Sponsorship Available: No
  • Schedule:


Posting Description

LECTURER AND DIGITAL LEARNING LEAD, ARTIFICIAL INTELLIGENCE AND DECISION-MAKING (AI+D), Electrical Engineering and Computer Science (EECS). The position oversees and leads the operation of the courses that comprise a new MIT online Artificial Intelligence and Decision-Making (AI+D) MicroMasters program. We are looking for candidates who share our passion for providing a quality online education in these extremely important and timely areas of study. This position both requires and benefits from involvement with other MIT faculty, staff, and researchers.

Responsibilities include:

  • Helping to develop, revise, and manage the courses in the above-listed subjects.
  • 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; planning and managing live exams using online proctoring technology. 
  • Leading both the 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.
  • Conducting data analysis, proposing and helping implement course revisions and improvements, and supporting other educational and research activities as part of the MicroMasters team.

About the Artificial Intelligence and Decision-Making (AI+D) Micromasters

This MicroMasters provides a sound and practical grounding in courses including probability, statistics, optimization, game theory, machine learning (including deep and reinforcement learning), and their many multi-modal applications. It is intended for students (often in the workforce) with good software skills who hope to extend their capabilities into application areas requiring artificial intelligence and automated decision-making. Students who complete the program will receive a Certificate and be eligible to apply for additional in-person training that will enable them to receive an MIT Masters Degree.

Job Requirements

REQUIRED: Master's degree in computer science or related field; some background in AI or data science; the 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, a track record of working independently and collaboratively, a 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, Operations Research, Mathematics, or a related field.  Proficiency in evaluating the effectiveness of learning materials and academic assessment.  Strong problem-solving / debugging skills and working knowledge or familiarity with machine learning, deep learning, statistical software, and analytics tools to analyze big data sets.  A demonstrated working knowledge of Python and other programming, statistical and AI 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.

To apply, candidates must submit a cover letter speaking to qualifications and preferred course assignments and a CV listing educational background, publications, talks, and other applicable experience. Applications will be considered until the position is filled.

Employment is contingent upon the completion of a satisfactory background check.

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