Tenure – Track Faculty Positions in Computing Health Planet

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
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…