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Massachusetts Institute of Technology
Cambridge, MA
Department of Materials Science and Engineering

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Tenure-Track Faculty Position

The Department of Materials Science and Engineering (DMSE) together with the Schwarzman College of Computing at the Massachusetts Institute of Technology (MIT) in Cambridge, MA seeks candidates for shared tenure track faculty positions in the area of "Health of the Planet" to begin September 1, 2023 or on a mutually agreed date thereafter.   The Department of Materials Science and Engineering and the Schwarzman College of Computing (SCC) are committed to fostering interdisciplinary research that can address grand challenges facing our society.   We welcome outstanding applicants with research and teaching interests that revolve around advances in integrated efforts for simulation, computation, machine learning and AI methods for materials fundamentals and technology innovation in sustainability-related domains.   In particular, this joint search seeks candidates who leverage computational approaches and data-driven methodologies to comprehend and influence systems-level environmental impacts across materials life cycles.   We seek candidates who will provide inspiration and leadership in research, contribute proactively to both undergraduate and graduate level teaching in the Materials Science and Engineering department and SCC.   DMSE 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, however, an untenured associate or senior faculty appointment is possible, commensurate with experience.

Materials innovations are at the core of our climate and sustainability crisis.   Materials must play a significant role enabling the unprecedented transition towards lower greenhouse gas emitting energy and production systems.   However, the discipline must also reduce the burden caused by materials across their life cycle along multiple dimensions of sustainability.   Solutions will require integrated research efforts that develop novel fundamental modeling, computation, machine learning and AI methods coupled to materials fundamentals and technological innovation.   This joint search seeks candidates in research areas that link data-driven methods to materials science and engineering in the context of the health of the planet.   We seek candidates who leverage computational methods and data-driven methodology to comprehend the systems-level responses across materials life cycles.

Candidates should be able to ground their course of study to the broader sustainability impact of the research and involve computing that deepens the fields understanding across length scales enabling advances in predictive and diagnostic capability spanning chemicals to factories to global economies.   Topics of interest include but are not limited to:

  • Transformative, resilient materials-driven solutions for clean air, waste management, water quality, and food, e.g., use of data-driven models and AI-embedded engineering for clean filtration, desalination, water management, agriculture, clean harvesting, and food security
  • Computing for materials design in water treatment, catalysis, separations, and renewable energy, e.g., computational and data-driven approach for materials design including energy conversion with renewable storage, efficient carbon capture, smart power systems, intelligent buildings and infrastructure materials
  • Sustainable materials synthesis, processing, and manufacturing, e.g.; AI-based design of devices, structures and systems that are energy-efficient, promote reuse and recycling of materials, reduce consumption, rapidly assess in-use implications, predict lifetimes and degradation pathways, or otherwise mitigate environmental impact on the planet and/or build resilience in adaptation to climate change
  • Computational methods to enhance characterization, experimentation (including high throughput and autonomous laboratory capability) and sensing in environment-relevant topics, efficient energy conversion, generation and transmission, storage technologies, and materials that operate in extreme environments
The successful candidate would have a shared appointment in both the Department of Materials Science and Engineering and 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 should hold a Ph.D. in Materials Science and Engineering, Mechanical Engineering, Electrical Engineering, Computer Science, Chemical Engineering, Engineering Physics, or a related field by the start date of employment.

To apply, please fill out the application at (https://faculty-searches.mit.edu/dmse_scc/register.tcl).   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 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 to MIT Faculty Search Portal by December 1, 2022: https://faculty-searches.mit.edu/letters

Send all materials not submitted on the website to:
Department of Materials Science & Engineering Search Committee
Massachusetts Institute of Technology
c/o dmse-scc-search@mit.edu
Room 13-5049
77 Massachusetts Avenue
Cambridge, MA 02139

Review of applications will begin immediately.

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.

We especially encourage minorities and women to apply because of MIT's strong commitment to diversity in engineering education, research and practice.

Questions?

For general questions, technical issues, or problems submitting documents, please contact Search-Admin@faculty-searches.mit.edu.

Questions? Please contact Search-Admin@Faculty-Searches.mit.edu