PhD position in Machine Learning for Engineering Design

100%, Zurich, fixed-term

The Laboratory for Intelligence in Design Engineering and Learning (IDEAL) in the Department of Mechanical and Process Engineering invites applications for one to two doctoral (Ph.D.) positions in the area of Machine Learning for Engineering Design under the guidance of Prof. Mark Fuge, the Chair of Artificial Intelligence in Engineering Design. The general area of the laboratory covers the study of Artificial Intelligence and Machine Learning in the context of Engineering Design problems in domains such as healthcare, power generation, aerospace, and robotics.

Project background

This is a general search and is not specific to a particular project so we are prioritizing scientific excellence and fit to the laboratory over any particular topic area. General areas of current research interest for the lab include, but are not limited to:

• Generative Models
• Transfer Learning
• Formal Systems and Program Analysis
• Self-Supervised Learning
• Intersection of Mathematical Topology and Machine Learning
• Agentic/Multi- Agent coordination for Engineering Design
• Industrial Robotics and multi-robot coordination
• Development of Engineering Benchmarks or Evaluation Frameworks
• Other emerging areas at the intersection of ML/AI and Engineering Design

Job description

As a Doctoral researcher, your responsibilities may include:

• Individual or collaborative work on research including writing publications and contributing toward individual or shared code bases
• Collaborating, where relevant, with partners from industry, academia, and national labs to translate real-world needs into scientific or technical questions
• Learning new skills in specialized graduate areas via courses and other educational offerings, or through self-learning
• Assisting with the teaching mission of the laboratory, which includes working with Masters and/or Bachelors thesis students as well as course assistance as needed
• Generally being a good lab citizen by assisting in various shared laboratory administrative tasks shared by the team

Profile

The following are some characteristics that may align well with the position:

• We are open to diverse educational backgrounds of applicants which can include engineering, mathematics, computer science, physics or other degree backgrounds
• Students in the lab typically have interests in or expertise in one of the following areas: Machine Learning, Optimization, Simulation or Robotics
• Having a strong publication record across either competitive journals or Computer Science conference venues is a plus, but not a requirement, especially for those with practical experience or non-traditional career paths
• Experience with High-Performance Computing (HPC) environments or Software Engineering best practices is a plus, but not a requirement
• You should possess strong English language skills and the ability to work successfully and collaboratively on diverse, multinational teams

We encourage candidates to apply even if they do not think they possess every point above, particularly for candidates who may not have had access to certain development opportunities. We will work with any selected candidates to develop targeted competencies on a personalized basis.

Workplace

We offer

You can look forward to:

• World-class research infrastructure and excellent working conditions guided by our common understanding of a supportive shared work culture
• Opportunities to work with a diverse, motivated and multicultural team in a creative research environment
• An rich intellectual environment within the lab and the university that includes top scholars from across the globe
• Support for personalized professional development and mentoring with the ability to build a strong support network for your future career and be part of a laboratory with a strong track record of placing employees into competitive research positions, professorships and industrial R&D

We value diversity and sustainability

Curious? So are we.

We look forward to receiving your online application through this portal and it should contain the following documents in PDF format (make sure your last name is on all the documents and in the file name):

• A Curriculum Vitae or Resume detailing your relevant past experience including a list of publications (if relevant).
• A Research Statement or Statement of Purpose describing why you are interested in pursuing a Ph.D. position (and in our lab in particular), what types of research topics related to the lab would interest you and what background or past experience you have that makes you well suited for those topics. (1-2 pages)
• A copy of your undergraduate and graduate transcripts.
• A short Cover Letter listing possible time windows you would be available during the weeks of March 16th and March 23rd for a Zoom interview, as well as your desired start date. This is to help us facilitate logistics and scheduling for the Zoom interviews, and will not affect candidate evaluation.
• Contact information for two references, which can be appended to the CV or provided as a separate PDF if you prefer. No reference letters are needed at the time of application, and we will notify you in advance if we intend to reach out to them or request letters.

For best consideration, please submit the above application by March 15th, 2026. We anticipate providing interviews and final decisions to candidates before April 1st. The start date can be determined upon mutual agreement with the selected candidate(s) to best account for their personal needs, but as a range we anticipate that the earliest start date could be during May 2026, with the latest state date being October 2026.

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about our lab can be found on our website . Questions regarding the position should be directed to Mrs Martina Koch, Adm. Assistant, Tel 044 632 45 16 or email E-Mail schreiben (no applications).

We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.