Tenure-track Assistant Professor in Decision-Making for Networked Infrastructure

Massachusetts Institute of Technology (MIT); Cambridge (MA); On-site; USD 143,000 - 147,000; Full time

Job summary

MIT in Cambridge, MA seeks tenure-track applicants for Assistant Professor positions in the Department of Civil and Environmental Engineering (CEE) and IDSS, to begin July 1, 2027. Fields include decision-making for networked infrastructure, with emphasis on learning, optimization, and control for real-world systems.

Successful candidates will teach, mentor, and lead research bridging CEE and IDSS, focusing on scalable, safe, and trustworthy infrastructure systems. Ph.D.

Qualifications

• Ph.D. in Civil/Environmental/Mechanical/Electrical/CS/OR/Statistics/Applied Mathematics or related field before start date.
• Excellent research record and potential for interdisciplinary collaboration.
• Ability to teach undergraduate and graduate courses.

Responsibilities

• Teach at the undergraduate and graduate levels and advise students.
• Conduct original scholarly research and develop course materials.
• Contribute to CEE and IDSS educational programs and cross-unit coordination.

Skills

Decision-making

Optimization

Control

ML for infrastructure

Education

Ph.D. in Civil/Environmental/Mechanical/Electrical/CS/OR/Statistics/Applied Mathematics or related field

Job description

The Department of Civil and Environmental Engineering (CEE), together with the Institute for Data, Systems, and Society (IDSS) at the Massachusetts Institute of Technology (MIT) in Cambridge, MA, seeks applicants for tenure-track faculty positions to begin July 1, 2027, or on a mutually agreed date thereafter. Appointment will be at the assistant professor level. In special cases, however, an untenured associate or senior faculty appointment may be possible, commensurate with experience.

We seek candidates who can make foundational contributions to the science and engineering of decision-making for networked infrastructure. We are interested in researchers developing learning, optimization, and control methods for infrastructure systems that sense, decide, and adapt - safely and at scale - with strong connections to real-world systems such as supply chains, energy, transportation, water, logistics, and other critical infrastructure networks.

Particular areas of interest include:

• Sequential decision-making at scale, including learning, optimization, and control under uncertainty across supply chains, energy systems, transportation, and logistics
• Hybrid physics and data models that combine first-principles physics with data, real-time sensing, state estimation, and rigorous uncertainty quantification
• Trustworthy AI for critical infrastructure, including foundations for safe operation, verification, guardrails, human oversight, and resilience to human-cyber-physical failures

We are especially interested in candidates who connect methodological advances in machine learning, operations research, control, statistics, or related fields to fundamental and consequential infrastructure problems. The successful candidate will help deepen the intellectual bridge between CEE and IDSS and contribute to the development of intelligent infrastructure systems in which physical dynamics, sensing, inference, decision-making, and control are integrated into a coherent engineering framework.

The successful candidate will demonstrate excellence in original research and a strong commitment to interdisciplinary education. Faculty responsibilities include: teaching at the undergraduate and graduate levels, advising students, conducting original scholarly research, developing course materials, and contributing to both CEE and IDSS educational programs. The normal teaching load is two subjects per year, with teaching responsibilities coordinated across the two units.

Applicants should hold a Ph.D. in Civil Engineering, Environmental Engineering, Mechanical Engineering, Electrical Engineering, Computer Science, Operations Research, Statistics, Applied Mathematics, or a related science or engineering field by the beginning of employment. Candidates from adjacent disciplines are encouraged to apply when their work advances the science and engineering of infrastructure decision-making.

The pay range for a 9-month academic appointment at the entry-level Assistant Professor rank (excluding summer salary): $143,000 – $147,000. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements. This pay range represents base pay only and does not include any other benefits or compensation.

Employment is contingent upon the completion of a satisfactory background check, including possible verification of any findings of misconduct or pending investigations from prior employers.

MIT is an equal employment 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, pregnancy, religion, disability, age, genetic information, veteran status, ancestry, or national or ethnic origin. See MIT’s full policy on Nondiscrimination (https://policies.mit.edu/policies-procedures/90-relations-and-responsibilities-within-mit-community/92-nondiscrimination). Know your rights: https://www.eeoc.gov/sites/default/files/2022-10/EEOC_KnowYourRights_screen_reader_10_20.pdf.