Career Opportunities at EECS

The Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science (EECS) in Cambridge, Massachusetts seeks candidates for faculty positions starting July 1, 2024, or on a mutually agreed date thereafter. We welcome outstanding applicants with research and teaching interests in any area of electrical engineering, computer science, and artificial intelligence and decision making. EECS believes that the intellectual, cultural and social diversity of our faculty, staff, and students is vitally important to the distinction and excellence of our academic and research programs. The Department seeks candidates who support our institutional commitment to ensuring that MIT is inclusive, equitable, and diverse.

Appointment will be at the assistant or untenured associate professor level. In special cases, a senior faculty appointment may be possible, commensurate with experience. Faculty duties include teaching at the undergraduate and graduate levels, research, and supervision of student research. Candidates should hold a Ph.D. in electrical engineering and computer science or a related field by the start of employment. Employment is contingent upon the completion of a satisfactory background check, including possible verification of any finding of misconduct (or pending investigation) from prior employers.

Candidates must register with the EECS search website at https://faculty-searches.mit.edu/eecs, and must submit application materials electronically to this website. Applications must include a cover letter, curriculum vitae, a research statement (2-4 pages) and a teaching statement (1-2 pages). In addition, candidates should provide a statement regarding their views on diversity, inclusion, and belonging, including past and current contributions as well as their vision and plans for the future in these areas. Each application should include the names and addresses of three or more individuals who will provide letters of recommendation. Letter writers should submit their letters directly to MIT, preferably on the website or by mailing to the address below. Complete applications should be received by December 1, 2023. Applications will be considered complete only when both the applicant materials and at least three letters of recommendation are received.

It is the responsibility of the candidate to arrange reference letters to be uploaded at https://faculty-searches.mit.edu/eecs by December 1, 2023.

Send all materials not submitted on the website to:

Professor Asu Ozdaglar
Department Head, Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Room 38-403
77 Massachusetts Avenue
Cambridge, MA 02139

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.

The Department of Political Science at the Massachusetts Institute of Technology (MIT) in Cambridge MA, together with the MIT Schwarzman College of Computing (SCC), seeks applicants for a position in the area of “Computation and Political Science” at the level of tenure-track Assistant Professor beginning July 1, 2024 (for the 2024–25 academic year), or as soon thereafter as possible. A PhD degree in political science, computer science, statistics, or another relevant field is required by the start of employment. We seek candidates whose research involves development and/or intensive use of computational and/or statistical methodologies, aimed at addressing substantive questions in political science. Areas of interest include methods for causal inference; AI/machine learning as applied to political questions; analysis and political implications of AI, big data, and computation; and other topics at the intersection of politics and computing. The successful candidate will have a shared appointment in both the Department of Political Science and SCC in either the Institute for Data, Systems, and Society or the Department of Electrical Engineering and Computer Science, depending on best fit. Faculty duties include conducting original research, and teaching and mentoring graduate and undergraduate students. The normal teaching load is three subjects per year (2+1 or 1+2). Candidates are expected to teach in both the Department of Political Science and educational programs of SCC.

Apply here: https://academicjobsonline.org/ajo/jobs/25219/apply

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. Applications should include a cover letter which addresses your research agenda and teaching interests, and how your past efforts and future plans will advance diversity, equity, and inclusion in your scholarship, teaching, and service. Also include a CV, writing sample(s), and three recommendations. Completed applications must be submitted by September 15, 2023. Employment is contingent upon the completion of a satisfactory background check, including verifying any finding of misconduct (or pending investigation) from prior employers.

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 here. Employment is contingent upon the completion of a satisfactory background check, including verifying any finding of misconduct (or pending investigation) from prior employers.

Digital Learning Lab Fellow – AI+DM MicroMasters
(Lecturer non-faculty)
Department of Electrical Engineering & Computer Science

Position Overview:

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.

Principal Duties and Responsibilities (Essential Functions**):
Course and Program design for the MicroMasters (35%)
• Work with faculty director to design and finalize program structure
• Work with course faculty (and OL learning engineer) to decide on course structure for the online platform, types of videos, educational exercises, and assessments etc.
• Find and recommend digital learning solutions as needed
• Support the faculty in the development of the online version of the courses as needed

Lead and manage the production teams for all courses in MM, to ensure each course is on time and within budget (35%)
• Assemble course production team for each course, with course faculty approval
• Decide on phases of production of all the courses
• Decide on tasks and timeline for team members in each team
• Facilitate and manage video production for course faculty, with help from MITx
• Other responsibilities as needed

Generate content and ensure quality of courses (20%)
• Train course team for content generation for edX
• Contribute in content as needed
• Review work by production team and facilitate review with faculty
.
Work and communicate with MITx/OL on both course and program level issues (10%)
• Collaboration around marketing, MM portal maintenance, etc., and facilitate communication between MITx/OL and course faculty and faculty director.
• Participation in Digital Learning Lab initiatives and attending cross-departmental Digital Learning Lab meetings.

Qualifications & Skills:
• A master’s degree in engineering or related field.
• Excellent organizational and management skills; track-record of working both independently and collaboratively; deadline-oriented attitude; attention to detail; flexibility and ability to adapt to a rapidly changing platform/environment; and an ability to deliver high quality results while managing multiple priorities.
• Excellent communication skills to conduct live webinars and the ability to build strong working relationships with teammates, faculty, and staff.

PREFERRED EDUCATION AND EXPERIENCE:
• 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.

** To comply with regulations by the American with Disabilities Act (ADA), the principal duties in job descriptions must be essential to the job. To identify essential functions, focus on the purpose and the result of the duties rather than the manner in which they are performed. The following definition applies: a job function is essential if removal of that function would fundamentally change the job.