Tenure-track faculty positions, Computing for Health of the Planet – MIT

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. 


Leave a Reply

Your email address will not be published. Required fields are marked *


This site uses Akismet to reduce spam. Learn how your comment data is processed.