Postdoctoral Associate in Civil/Structural Engineering
Civil and Environmental Engineering, to work in the area of sensing, data analytics, and computational modeling. Will lead the research efforts on two projects in structural health monitoring in the Laboratory for Infrastructure Science and Sustainability (LISS)--data interferometry for field monitoring and ground motion modeling and structural monitoring of tall buildings for safety and reliability assessment.
The data interferometry research will involve developing novel data interferometry techniques to address structural and crustal monitoring problems with dense sensing networks, in close collaboration with the MIT Department of Earth, Atmospheric and Planetary Sciences team.
The ground motion and structural monitoring research will involve developing combined data-driven and physics model-based algorithms for reliability and resilience assessment of tall buildings.
Will be responsible for performing a leadership role and providing the support and management skills necessary to accomplish the objectives of the projects; and assisting the principal investigator with preparing other research project proposals, delivering timely project reports and presentations, and publishing high quality journal papers.
REQUIRED: a Ph.D. in civil/structural engineering and an engineering mechanics-related field with experience in seismic interferometry, computational modeling, sensing and data analytics in structural monitoring, and probability analysis; ability to manage projects and meet competing deadlines; and excellent interpersonal and oral and written communication skills. One year of related postdoctoral experience is preferred.
In addition to applying via the MIT HR website, please submit a CV (with the contact information for three references) to Prof. Oral Buyukozturk at firstname.lastname@example.org.
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.