Massachusetts Institute of Technology
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Postdoctoral Associate in Machine Learning for Computer-Aided Design and Engineering Design at MIT Massachusetts Institute of Technology in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Available
Deadline
Oct 20, 2025
Country
United States
University
Massachusetts Institute of Technology

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About this position
Massachusetts Institute of Technology (MIT) is advertising a Postdoctoral Associate position in Mechanical Engineering within the Design Computation and Digital Engineering (DeCoDE) laboratory in Cambridge, Massachusetts, United States.
The project focuses on machine learning models for Computer-Aided Design (CAD) and Engineering Design, with an emphasis on developing novel methods and algorithms for the engineering design domain. The postdoc will work under the guidance of Dr. Faez Ahmed and contribute to research, proposal development, and collaborative team-based work in the lab.
Preferred academic background includes a Ph.D. in computer science, mechanical engineering, applied mathematics, or a related field. Strong research experience in machine learning / AI algorithm development is required, especially in deep generative models and/or graph neural networks. The posting notes that domain knowledge of mechanical engineering problems is not required, but the ability to transfer ML expertise to engineering problems is expected.
Application materials: a single PDF with a cover letter, CV, statement of proposed research (including novel directions for the DeCoDE lab), and one peer-reviewed publication. Three letters of reference will be required later in the interview process.
Deadline shown in the post: 2025-10-20. More information about the lab is available at the DeCoDE website.
Funding details
Available
What's required
Ph.D. in computer science, mechanical engineering, applied math, or a related field is required. Applicants should have significant research experience in machine-learning/AI algorithm development, especially deep generative models and/or graph neural networks. Domain knowledge of mechanical engineering problems is not required, but the ability to transfer knowledge to engineering problems is expected. Application materials include a cover letter with qualifications, current research interests, and expertise; CV; a statement of proposed research describing novel directions aligned with the applicant's expertise; one peer-reviewed publication; and three letters of reference during the interview process.
How to apply
Prepare a single PDF containing the cover letter, CV, proposed research statement, and one peer-reviewed publication. Submit via the application link provided on the posting. Three reference letters will be requested during the interview process.
More information can be found here
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