Lecturer Computing Education and AI Initiative

The MIT Schwarzman College of Computing and Department of Electrical Engineering and Computer Science (EECS) is seeking a Lecturer to contribute to its computing education initiatives, which bring together the goals of the Common Ground for Computing Education and other related programs, such as the AI Educators Pilot initiative. The Common Ground for Computing Education is an institute-wide academic effort that brings together faculty across MIT to develop and deliver interdisciplinary subjects integrating computing with diverse academic disciplines, with the goal of expanding computational thinking throughout the curriculum. The AI Educators Pilot initiative is a program designed for external faculty and other instructors that engages participants through workshops and collaborative activities to build expertise in artificial intelligence and support the integration of AI concepts and applications into their teaching.

Position Overview

Lecturer and Computing Learning Lead, Schwarzman College of Computing (SCC) and Department of Electrical Engineering and Computer Science (EECS), will support the delivery and development of curricular content for core computing education in the College, primarily offered with EECS. This includes advancing the Common Ground for Computing Education and efforts that extend MIT’s impact. The role has an emphasis on interdisciplinary computing education, curriculum design, and instructional innovation. The lecturer will play a central role in translating foundational computing and AI concepts into accessible, domain-relevant learning experiences for students.

Principal Duties and Responsibilities

• Serve as instructor or co-instructor for core computing and AI classes in the Common Ground.
• Help develop online classes and class materials building on Common Ground classes.
• Deliver lectures, lead recitations, and hold office hours.
• May serve as a primary instructor for one or more classes.
• Help develop, revise, and manage courses and related materials, including digital and online learning components where applicable.
• Manage course materials and related content; design, build, and optimize learner assessment tools, such as problem sets, exams, and other activities.
• Lead teaching assistants or other course staff.
• Support learner communication, performance tracking, and exam administration for live or online course offerings, including coordination of online proctoring technology as appropriate.
• Conduct data analysis on learning materials and outcomes; propose and help implement course revisions and improvements; and support related educational and research activities.
• Engages with students and/or program participants to support learning and academic success.
• Contribute to interdisciplinary computing education efforts across departments.
• Support the development and refinement of courses that integrate computing with other disciplines.
• Evaluate the effectiveness of courses and pedagogical approaches by working with other instructors and following up on learner feedback. 
• Assist in developing, maintaining, and updating the education strategy, and particularly any digital learning strategy.
• Contribute to building a community of educators integrating AI into their teaching.

Supervision Received

Will report to the SCC Deputy Dean for Academics, and the EECS and SCC Education Officer.

Supervision Exercised

Supervises Teaching and Laboratory Assistants and other course staff.

Qualifications & Skills

• PhD in Computer Science, Statistics, Operations Research, Applied and Computational Mathematics, or related field.
• Proficiency in evaluating the effectiveness of learning materials and academic assessment.
• Significant successful teaching experience in related undergraduate courses.
• A demonstrated interest in educational innovation.
• 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. 
• Strong communication and collaboration skills.

Preferred Qualifications

• Background in AI or related areas
• Experience in curriculum development or educational initiatives
• Experience with HTML and LaTeX. 
• Minimum of 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.

Appointment Details

The position will be a 12-month appointment, with potential for appointment extensions.

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.
 
Please note that only applications submitted via the official MIT Career Portal will be considered. 

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