The Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science (EECS) seeks candidates for faculty positions starting July 1, 2023, 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.

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, 2022. 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, 2022.

Send all materials not submitted on the website to:

Professor Asu Ozdaglar
Department Head, Electrical Engineering and Computer ScienceMassachusetts 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 Broad Institute (Cambridge, MA) and the Department of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (Cambridge, Massachusetts) seek applicants for a tenure-track position at the Assistant or un-tenured Associate Professor level, effective July 1, 2023, or as soon as possible thereafter.  Rank will be determined based on qualifications and experience. 

We welcome outstanding applicants with research and teaching interests in any area of machine learning, artificial intelligence and/or statistics that could drive the frontier of biomedical research at any scale (proteins, cells, tissues or organisms). The successful candidate will be a faculty member in the Department of EECS at MIT and a Broad Core Institute Member.

We believe 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. We seek candidates who support our institutional commitment to ensuring that the Broad Institute and MIT are inclusive, equitable, and diverse.

Successful applicants are expected to share our commitment to undergraduate and graduate education by teaching courses and supervising graduate and undergraduate research, as well as develop and lead a vibrant, independent research program that would benefit from being in the Broad Institute environment.  

Candidates are expected to have had formal graduate training and research focus in the computational sciences (e.g., as evidenced by their publication record), and hold a PhD (or equivalent terminal degree) in the field of computer or mathematical sciences, engineering (biological, chemical, etc.), or a related field by the start of employment.

Complete applications should be received by January 1, 2023. Applications include a cover letter, curriculum vitae, research statement (2-4 pages), and teaching statement (1-2 pages).  In addition, candidates should provide a statement on diversity, inclusion, and belonging, including past and current contributions as well as their vision and plans for the future in these areas (1-2 pages). Application materials should be submitted to https://faculty-searches.mit.edu/bree/ 

Completed application review will begin after January 1, 2023.

MIT and Broad are equal employment opportunity employers.  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.

Massachusetts Institute of Technology, Mathematics

Position ID: MIT–FACQC [#20993]
Position Title: Faculty (Theoretical Aspects of Quantum Computing)
Position Type: Other
Position Location: Cambridge, Massachusetts 02139-4307, United States [map]
Subject Area: Mathematics
Application Deadline: 2022/12/15 11:59PM* (posted 2022/10/17, updated 2022/10/06)
Position Description:   Apply    

Application Materials Required:

Submit the following items online at this website to complete your application:

• Cover letter
• Curriculum Vitae
• Research statement
• Publication list
• Broader Impact Statement
• Three reference letters (to be submitted online by the reference writers at this site )

And anything else requested in the position description.

Further Info:

math.mit.edu

617-258-7186

77 Massachusetts Avenue
Building 2, Room 106
Cambridge, MA 02139

Assistant Professor/Associate without Tenure (tenure track): Artificial Intelligence (AI) and Human Experience
Massachusetts Institute of Technology: School of Architecture and Planning: Program in Media Arts and Sciences
Location
MIT Media Lab, Cambridge, Massachusetts
Open Date
Sep 19, 2022

Deadline
Nov 15, 2022 at 11:59 PM Eastern Time
Description
The Program in Media Arts and Sciences (MAS) and the MIT Schwarzman College of Computing (SCC) at the Massachusetts Institute of Technology (MIT) Cambridge, Massachusetts invite applications for a faculty position in the area of “Artificial Intelligence (AI) and Human Experience.” We welcome outstanding applicants with research and teaching interests who have demonstrated innovation in AI algorithm and tool development together with excellence in evaluating and shaping human experience using AI systems. Human experience research is expected to include the objective measurement of social-emotional data during human-computer interaction, the design and evaluation of AI algorithms that adapt to individuals for improving both human experience and performance of the AI methods, as well as addressing of related ethics and alignment aspects. MAS and SCC believe 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. We seek candidates who support our institutional commitment to ensuring that MIT is inclusive, equitable, and diverse. The appointment will be at the assistant or untenured associate professor level.

The successful candidate will have a shared appointment in both MAS and also SCC, in either the Department of Electrical Engineering and Computer Science (EECS) or the Institute for Data, Systems, and Society (IDSS). Faculty duties will include classroom teaching in topics related to AI and Human Experience, conducting original scholarly research, supervising and mentoring students, and playing an active role in shaping the academic work and cultures of both the MAS and SCC research communities. Candidates are expected to teach in both MAS and SCC-relevant curricula, which include both graduate and undergraduate classes.

The appointment will be at the assistant or untenured associate professor level.

Qualifications

Candidates should have a strong record of research, a willingness to take risks, a desire to look beyond traditional disciplines, and a dedication to making a difference in the world. Applicants should hold a doctoral degree in media arts and sciences, computer science, electrical engineering, a field related to AI and the Human Experience or a related field by the start of employment, and should have a track record of authoring or co-authoring peer-reviewed publications in AI and human experience at the time of application.

Application Instructions

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 via the application website or by mailing to the address below. Complete applications should be received by November 15, 2022. Applications will be considered complete only when both the applicant materials and at least three letters of recommendation are received.

Equal Employment Opportunity Statement

Position ID:	MIT–EAPS–EAPS_SCC [#23023]
Position Title:	Assistant Professor
Position Type:	Tenured/Tenure-track faculty
Position Location:	Cambridge, Massachusetts 02139, United States [map]
Subject Areas:	Atmospheric Science Oceanography Climate Earth and Environmental Sciences / Earth science
Appl Deadline:	2022/12/01=8 11:59PM (posted 2022/09/29)
Position Description:	Apply

The Department of Earth, Atmospheric and Planetary Sciences (EAPS) and the MIT Schwarzman College of Computing (SCC) at the Massachusetts Institute of Technology (MIT) Cambridge, Massachusetts, invite applications for a faculty position in the broad area of “Health of the Planet”. We seek candidates committed to advancing our understanding of processes that affect the Earth and its habitability, particularly through using and/or developing innovative computational and/or inference methods. Areas of scientific interest include but are not limited to climate, the environment, and natural hazards. Our intent is to hire at the tenure-track assistant professor level, but senior appointments may be considered in special cases, commensurate with experience. Faculty duties include conducting original scholarly research and teaching and mentoring at the graduate and undergraduate levels. Candidates are expected to teach in EAPS and in educational programs of SCC.

EAPS is an academic community of approximately 40 faculty, 100 research staff (including postdocs), and 180 students, who study integrated aspects of Earth and planetary sciences, including through partnership with the MIT-Woods Hole Oceanographic Institute (WHOI) Joint Program. The successful candidate will have a shared appointment in EAPS and SCC –- and within SCC, either in the Department of Electrical Engineering and Computer Science (EECS) or the Institute for Data, Systems, and Society (IDSS). EAPS and SCC are committed to academic excellence and to fostering an equitable and inclusive environment for a diverse faculty and academic community. We seek outstanding scientists who have the potential for innovation and leadership in research, bring strong commitment to teaching and mentoring undergraduate and graduate students, and share our Principles of Community.

A complete application should include (1) a cover letter; (2) curriculum vitae, (3) 1-3 page summary of current and future research directions; (4) 1-3 page description of teaching and mentoring experience and/or future plans, including contributions to fostering diversity, equity, and belonging and (5) at least three letters of recommendation.

A Ph.D. in Earth or other natural sciences, applied mathematics, computer science, or a related field is required by the start of employment.

Applications should be submitted by no later than December 8, 2022 for full consideration.

Search Contact: Ms. Karen Fosher, HR Administrator, EAPS, 54-924 Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139-4307, email: kfosher@mit.edu 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.

Application Materials Required:

Submit the following items online at this website to complete your application:

• Cover letter
• Curriculum Vitae
• Research statement
• Teaching and DEI Statement
• Three reference letters (to be submitted online by the reference writers at this site )

And anything else requested in the position description.

Further Info:

https://eapsweb.mit.edu/

617-253-2132

Massachusetts Institute of Technology
EAPS, 54-924
77 Massachusetts Avenue
Cambridge MA 02139-4307

FACULTY POSITIONS in Computing for Health of the Planet

in Mechanical Engineering and Schwarzman College of Computing Massachusetts Institute of Technology

Cambridge, MA

The Massachusetts Institute of Technology (MIT) Department of Mechanical Engineering together with the Schwarzman College of Computing seeks candidates for tenure-track faculty positions in Computing for Health of the Planet to start July 1, 2022 or on a mutually agreed date thereafter. The search is for candidates to be hired at the assistant professor level; under special circumstances, however, an untenured associate or senior faculty appointment is possible, commensurate with experience.

The health of the planet is one of the most important challenges facing humankind today. The need for a sustainable planet demands integrated research efforts that develop novel fundamental modeling, computation, machine learning and AI methods with technological innovation. A creative mens et manus approach is essential to ensure the health and security of our environment.

We seek candidates who have skills in computing and data-driven science and engineering, for applications and solutions related to the health of the planet. Topics include but are not limited to:

• Intelligent environmental monitoring and forecasting, e.g., fundamental and applied research in integrating dynamical models, machine learning, and physical systems for sensing, forecasting, and risk assessment of environmental hazards, such as sea-level change, flooding events, coastal pollution, heat waves, biodiversity threats, and adverse effects on human health
• AI-driven solutions for climate change mitigation and adaptation, e.g., computational and robotic systems, integrated smart sensors and dynamics, and deep learning methods to explore, utilize and protect our environment
• Sustainable mobility and transportation, e.g., use of data for estimation, prediction, autonomy, or control relevant to autonomous vehicles, clean transports, and ocean environments and systems
• Resilient solutions for clean air, usable water, and food, e.g., use of data-driven models and AI-embedded engineering for clean filtration, desalination, water management, smart irrigation, digital agriculture, sustainable aquaculture, clean harvesting, and food security
• Computing for sustainable and renewable energy, e.g., computational and data-driven approach for energy conversion with renewable storage, efficient carbon capture, smart power systems, low emission propulsion, green buildings
• Smart sustainable manufacturing and design, e.g., computing and data-driven process development, control, and optimization; discovery of new materials; AI-based design of devices, structures and systems that are energy-efficient, promote reuse and recycling of materials, reduce consumption, or otherwise mitigate climate change and environmental impact on the planet

Candidates should possess fundamental skills in one or more of the following areas: learning for dynamics, nonlinear dynamical systems, closure models, computational modeling, scientific machine learning, high dimensional statistics and optimization, science of autonomy, intelligent systems, smart sensing, computing devices, decision theory, risk analysis, and data-driven science and engineering.

The Department of Mechanical Engineering and the Schwarzman College of Computing (SCC) are committed to fostering interdisciplinary research that can address grand challenges facing our society. We are especially interested in qualified candidates who can contribute, through their research, teaching, and/or service, to the diversity and excellence of the academic community. We seek candidates who will provide inspiration and leadership in research, contribute proactively to both undergraduate and graduate level teaching in the Mechanical Engineering department and SCC. The successful candidate would have a shared appointment in both the Department of Mechanical Engineering and also the Schwarzman College of Computing, in either the Department of Electrical Engineering and Computer Science (EECS), or in the Institute for Data, Systems, and Society (IDSS). Candidates can also become members of the Center for Computational Science and Engineering (CCSE) and of other groups at MIT.

Faculty duties include teaching at the undergraduate and graduate levels, advising students, conducting original scholarly research and developing course materials at the undergraduate and graduate levels. Candidates must hold a Ph.D. in Engineering, Physics, Data Science, Computer Science, or Applied Mathematics or a similar discipline by the beginning of employment.

Applications must include a cover letter, curriculum vitae, 2–3 pages statement that explicitly highlights how their research has and/or will contribute to the health of the planet, as well as corresponding teaching interests and goals. In addition, candidates should provide a statement regarding their views on diversity, equity, inclusion, and belonging, including past and current contributions as well as their vision and plans for the future in these areas. Approaches to fostering an inclusive environment including but not limited to teaching, mentoring, and affirming diverse viewpoints, are encouraged to be discussed. They should also provide copies of no more than three publications. They should also arrange for four individuals to submit letters of recommendation on their behalf. This information must be entered electronically at the following site: https://school-of- engineering-faculty-search.mit.edu/meche/register.tcl by December 15, 2021 when review of applications will begin.

MIT is an equal-opportunity/affirmative action employer. The Department of Mechanical Engineering with the Schwarzman College of Computing are keenly interested in diversifying its faculty and encourages applications from candidates from historically underrepresented group(s) in higher education to apply. Women and underrepresented minorities are especially encouraged to apply.

Massachusetts Institute of Technology, Music and Theater Arts

Position ID:	MIT–MTA–MUSICTECH [#23552]
Position Title:	Assistant Professor in Music Technology and Computation
Position Type:	Tenured/Tenure-track faculty
Position Location:	Cambridge, Massachusetts 02139, United States [map]
Subject Area:	Music Technology
Appl Deadline:	2023/01/01 11:59PM (posted 2022/11/02)
Position Description:	Apply

Application Materials Required:

Submit the following items online at this website to complete your application:

• Cover letter
• Curriculum Vitae
• Teaching statement
• Two reference letters (to be submitted online by the reference writers at this site )

And anything else requested in the position description.

Further Info:

https://mta.mit.edu/music

(617) 253-3210

Massachusetts Institute of Technology
Music & Theater Arts
Cambridge, MA 02139-4037

Junior faculty / Tenure-track or similar

Workload        Full time

Vacancies        1

Location          Cambridge, Massachusetts, United States

Start date        July 2022

Job description

MASSACHUSETTS INSTITUTE OF TECHNOLOGY, Department of Linguistics and Philosophy, Cambridge, MA. One or more tenure track positions, at the rank of Assistant Professor, effective July 1, 2022 or as soon as possible thereafter. Area of Specialization: Philosophical issues related to computing OR moral/political philosophy, with interest in the ethics of computing. Area of Competence: Moral/political philosophy. Rank: Assistant Professor. Faculty responsibilities include teaching three graduate and/or undergraduate courses per year, or equivalent, semester system. Applicants should have a PhD in Philosophy or related field at start of employment. The position involves shared responsibilities with MIT’s Schwarzman College of Computing, including teaching within the College. Tenure home will be in the Department of Linguistics and Philosophy. MIT is an equal opportunity employer committed to building a culturally diverse intellectual community, and strongly encourages applications from women and minority candidates. The Department seeks candidates who support our institutional commitment to ensuring that MIT is inclusive, equitable, and diverse. The deadline for this position is October 29, 2021.

Apply online here: https://academicjobsonline.org/ajo/jobs/19256

How to apply

Application type         Online

Instructions

Applicants should submit cover letter, CV, three confidential letters of reference, and a sample of written work in area of specialization. Applications and supporting materials should be submitted online.

Web address to apply https://academicjobsonline.org/ajo/jobs/19256

Hard deadline Jan 1, 2023

Massachusetts Institute of Technology, Earth, Atmospheric & Planetary Sciences

Position ID:	MIT–EAPS–EAPS_SCC [#20816]
Position Title:	Assistant Professor
Position Type:	Tenured/Tenure-track faculty
Position Location:	Cambridge, Massachusetts 02139, United States [map]
Subject Areas:	Atmospheric Science Oceanography Climate Earth and Environmental Sciences / Earth science
Appl Deadline:	2022/01/31 11:59PM (posted 2021/12/15)
Position Description:	Apply

Application Materials Required:

Submit the following items online at this website to complete your application:

• Cover letter
• Curriculum Vitae
• Research statement
• Teaching and DEI Statement
• Three reference letters (to be submitted online by the reference writers at this site )

And anything else requested in the position description.

Further Info:

https://eapsweb.mit.edu/

Karen Fosher ( kfosher@mit.edu )

617-253-2132

Massachusetts Institute of Technology
EAPS, 54-924
77 Massachusetts Avenue
Cambridge MA 02139-4307

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.

Supervision Received:
Will report to the Denny Freeman, Education Officer, Chair
Supervision Exercised:
Program Coordinator

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.