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Postdoctoral Position in Machine Learning for Engineering Design, Robotics, and AI-Guided Optimization ETH Zurich in Switzerland
Degree Level
Postdoc
Field of study
Computer Science
Funding
The position is a full-time, 100% fixed-term employment appointment with an anticipated duration of approximately two years, initially contracted for one year with possible extensions based on performance. ETH Zurich offers excellent working conditions, research infrastructure, professional development and mentoring, and flexibility in time and location, including possible home working from Switzerland. No specific salary or stipend amount is stated.
Deadline
Jan 15, 2027
Country
Switzerland
University
ETH Zurich
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About this position
ETH Zurich’s Laboratory for Intelligence in Design Engineering and Learning (IDEAL), within the Department of Mechanical and Process Engineering, invites applications for a postdoctoral position in machine learning for engineering design. The researcher will work under the guidance of Prof. Mark Fuge, Chair of Artificial Intelligence in Engineering Design, in a growing team developing AI methods and scientific infrastructure for engineering research.
The research builds on the laboratory’s work in AI-guided design, inverse design, optimization, automated robotic assembly, automated design for assembly, and engineering-design benchmarking through the EngiBench and EngiOpt initiatives. The project will investigate how physical experiments can be integrated with digital and AI-driven models, alongside formal verification of software systems. Potential directions include generative modeling, robotics, computational simulation, program analysis and synthesis, autoformalization, and formal verification of mechanical systems.
The postdoctoral researcher will help shape the scientific vision and direction of future laboratory efforts. Activities may include developing novel algorithms for engineering design, deploying simulation and algorithm pipelines on high-performance computing infrastructure, collaborating with industry, academic, and national-laboratory partners, and contributing to scientific research publications and proposals. The role also offers opportunities to coordinate development efforts, help establish digital and physical laboratory infrastructure, and contribute to lab-wide processes.
The researcher will collaborate with Ph.D. students, postdoctoral researchers, scientific staff, software developers, and other members of ETH Zurich’s research community. Depending on the research focus, the position may involve supervising students, contributing to relevant teaching, presenting work at conferences and workshops, and supporting a diverse, multinational research environment. The appointment provides opportunities to develop leadership, laboratory-operation, software-development, and independent-research experience.
Funding details
The position is a full-time, 100% fixed-term employment appointment with an anticipated duration of approximately two years, initially contracted for one year with possible extensions based on performance. ETH Zurich offers excellent working conditions, research infrastructure, professional development and mentoring, and flexibility in time and location, including possible home working from Switzerland. No specific salary or stipend amount is stated.
What's required
Applicants should hold a Ph.D. in Mechanical Engineering, Computer Science, Applied Mathematics, Robotics, or a related field, with an excellent publication record in archival journals, computer science or robotics conferences, or other competitive venues. Expertise in one or more of Machine Learning, Robotics, computational simulations such as CFD or FEA, engineering problems, High-Performance Computing, or software engineering and analysis is expected. Strong English-language skills and the ability to collaborate effectively in diverse, multinational teams are required. Preferred qualifications include experience with modern Machine Learning or HPC tools such as Python or Julia libraries including PyTorch and JAX, packaging and deploying simulation or ML code on distributed servers and HPC clusters, professional software development practices, and leadership of collaborative code-development efforts. Experience in robotics, manufacturing, computer vision or language models, formal verification, and software analysis is advantageous. Applicants should address relevant ETH Zurich core competencies and examples in their cover letter.
How to apply
Submit an online application through the ETH Zurich application portal by January 15, 2027. Upload PDF versions of a maximum two-page cover letter addressed to Prof. Mark Fuge, a CV including publications, contact information for two references, and a one- to two-page research statement. Include your last name on every document and in each filename; applications by email or post are not accepted.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.