
Lecturer and Computing Learning Lead
Massachusetts Institute of Technology
Cambridge, MAFull-time$125–150K/yrSeen 4w agoSeen in employer's feed 3 days ago
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Job overview
The Lecturer and Computing Learning Lead will support delivery and development of core computing curriculum at MIT, advance interdisciplinary computing education initiatives, and translate foundational computing and AI concepts into accessible, domain-relevant learning experiences for undergraduate students.
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Full job description
Lecturer and Computing Learning Lead
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Job Number: 26006
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Functional Area: Academic (non-faculty)
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Department: Schwarzman College of Computing
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School Area: Schwarzman College of Computing
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Pay Range Minimum: $125,000
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Pay Range Maximum: $150,000
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Employment Type: Full-Time
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Employment Category: Exempt
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Visa Sponsorship Available: No
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Schedule: Monday-Friday 8 Hours a Day
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Pay Grade: No Grade
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Posting Description
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.
The full job description is available here: https://computing.mit.edu/lecturer/
Job Requirements
REQUIRED: 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; and strong communication and collaboration skills.
This is a nine-month academic-year appointment with two additional months of required summer work and corresponding summer salary.
The initial appointment will be for two years, with the possibility of renewal or extension.
9/3/2026
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