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Tenure – Track Faculty Positions in Computing for Health of the Planet

Massachusetts Institute of Technology (MIT)
Cambridge, Massachusetts
Closing date
Dec 27, 2021

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Job Type
Full time

Tenure – Track Faculty Positions in Computing for Health of the Planet

Massachusetts Institute of Technology

Department of Mechanical Engineering and Schwarzman College of Computing

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


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


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- by December 15, 2021 when review of applications will begin.



MIT is an equal opportunity employer.  We value diversity and strongly encourage applications from individuals from all identities and backgrounds. All qualified applicants will receive equitable consideration for employment based on their experience and qualifications, 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.

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