Mark Fuge
Just added
1 days ago
PhD position in Machine Learning for Engineering Design ETH Zürich in Switzerland
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Mar 15, 2026
Country
Switzerland
University
ETH Zürich

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About this position
The Laboratory for Intelligence in Design Engineering and Learning (IDEAL) at ETH Zürich’s Department of Mechanical and Process Engineering is offering one to two PhD positions in Machine Learning for Engineering Design, supervised by Prof. Mark Fuge, Chair of Artificial Intelligence in Engineering Design. The IDEAL lab investigates the application of artificial intelligence and machine learning to engineering design problems across domains such as healthcare, power generation, aerospace, and robotics. This general search prioritizes scientific excellence and fit to the laboratory, with current research interests including generative models, transfer learning, formal systems and program analysis, self-supervised learning, mathematical topology intersecting with machine learning, agentic/multi-agent coordination, industrial robotics, and the development of engineering benchmarks and evaluation frameworks.
As a doctoral researcher, you will engage in individual or collaborative research, contribute to publications and code bases, collaborate with industry and academic partners, learn new skills through courses or self-learning, assist with teaching and mentoring Masters and Bachelors students, and participate in shared laboratory administrative tasks. The lab values diverse educational backgrounds, including engineering, mathematics, computer science, and physics. Preferred expertise includes machine learning, optimization, simulation, or robotics. A strong publication record is advantageous but not required, and practical experience or non-traditional career paths are welcomed. Experience with high-performance computing or software engineering best practices is a plus. Strong English language skills and the ability to work collaboratively in multinational teams are essential.
ETH Zürich offers world-class research infrastructure, excellent working conditions, and a supportive, multicultural environment. The university is committed to diversity, equality of opportunity, and sustainability, fostering a climate-neutral future. The IDEAL lab provides personalized professional development, mentoring, and a strong support network, with a track record of placing graduates in competitive research, professorships, and industrial R&D positions.
To apply, submit your application online via the provided portal. Required documents include a CV or resume (with publications if relevant), a research statement (1-2 pages), undergraduate and graduate transcripts, a cover letter listing interview availability and desired start date, and contact information for two references. No reference letters are needed at the time of application. For best consideration, apply by March 15th, 2026. Interviews and final decisions are expected before April 1st, with start dates ranging from May to October 2026. Applications via email or postal services will not be considered. For further information, visit the lab website or contact Mrs Martina Koch ([email protected]) for administrative questions (not applications).
ETH Zürich is a leading university in science and technology, renowned for excellent education, cutting-edge research, and global impact. With over 30,000 people from more than 120 countries, ETH Zürich promotes independent thinking and inspires excellence, working together to address global challenges.
Funding details
Available
What's required
Applicants should have a degree in engineering, mathematics, computer science, physics, or a related field. Interests or expertise in machine learning, optimization, simulation, or robotics are preferred. A strong publication record in competitive journals or computer science conference venues is a plus, but not required. Experience with high-performance computing environments or software engineering best practices is beneficial but not mandatory. Strong English language skills and the ability to work collaboratively in diverse, multinational teams are required. Candidates from non-traditional backgrounds or with practical experience are encouraged to apply. Transcripts, CV, research statement, cover letter with interview availability, and contact information for two references are required for application.
How to apply
Submit your application online via the provided portal. Include your CV, research statement, transcripts, cover letter with interview availability, and contact information for two references in PDF format. Applications via email or postal services will not be considered. For best consideration, apply by March 15th, 2026.
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