PhD Candidate in Machine Learning for Engineering Design / PhD Candidate in Machine Learning for Engineering Design

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 laboratory focuses on the application of Artificial Intelligence and Machine Learning to Engineering Design problems in areas such as healthcare, power generation, aerospace, and robotics.

Project Background

This is an open search prioritizing scientific excellence and fit within the laboratory. Current research interests 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:

• Conducting individual or collaborative research, including writing publications and contributing to codebases.
• Collaborating with industry, academia, and national labs to translate real-world needs into scientific or technical questions.
• Learning new skills in specialized graduate areas through courses and self-study.
• Assisting with the teaching mission of the laboratory, working with Master's and/or Bachelor's thesis students.
• Contributing to shared laboratory administrative tasks.

Profile

We welcome applicants from diverse educational backgrounds such as engineering, mathematics, computer science, or physics. Ideal candidates will typically have interests or expertise in areas like:

• Machine Learning
• Optimization
• Simulation
• Robotics

A strong publication record in competitive journals or conferences is a plus, especially for those with practical experience or non-traditional backgrounds. Experience with High-Performance Computing (HPC) or software engineering best practices is also valued. Strong English language skills and the ability to work collaboratively in diverse, multinational teams are essential.

Workplace

Join us in a supportive and innovative environment.

We Offer

You can look forward to:

• World-class research infrastructure and excellent working conditions.
• Opportunities to engage with a diverse, motivated, and multicultural team in a creative research setting.
• An intellectually stimulating environment that includes top scholars from around the globe.
• Personalized professional development and mentoring to build a strong support network for your future career.

We Value Diversity and Sustainability

ETH Zurich promotes an inclusive culture, emphasizing equality of opportunity and respect for the rights and dignity of all staff and students. Sustainability is a core value as we strive towards a climate-neutral future.

Curious? So Are We.

Apply online using the form below. Only applications matching the job profile will be considered.

About ETH Zurich

ETH Zurich is one of the world's leading universities specializing in science and technology, renowned for excellent education and cutting-edge research. With more than 30,000 individuals from over 120 countries, we create an environment that inspires excellence and fosters independent thinking. Located in the heart of Europe, we collaborate to tackle global challenges for today and tomorrow.