PhD Candidate / PhD Candidate

PhD Position in Machine Learning for Engineering Design

Location: Zurich, 100%, Fixed-Term

The Laboratory for Intelligence in Design Engineering and Learning (IDEAL) within the Department of Mechanical and Process Engineering invites motivated candidates to join us for one to two doctoral (Ph.D.) positions in the realm of Machine Learning for Engineering Design, under the mentorship of Prof. Mark Fuge, the Chair of Artificial Intelligence in Engineering Design. Our laboratory focuses on the application of Artificial Intelligence and Machine Learning to Engineering Design problems across various domains such as healthcare, power generation, aerospace, and robotics.

Project Background

This is a general search prioritized on scientific excellence and fit within our laboratory, rather than a specific project. Current research interests in the lab include, but are not limited to:

• Generative Models
• Transfer Learning
• Formal Systems and Program Analysis
• Self-Supervised Learning
• 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
• Emerging areas at the intersection of ML/AI and Engineering Design

Job Description

As a Doctoral researcher, your responsibilities may encompass:

• Conducting individual or collaborative research, which includes writing publications and contributing to codebases.
• Collaborating with partners from industry, academia, and national labs to address real-world challenges through scientific or technical questions.
• Acquiring new skills in specialized graduate areas via courses or self-directed learning.
• Assisting with the lab's teaching mission, which includes mentorship of Master's and/or Bachelor's thesis students, and providing course assistance when needed.
• Actively contributing to various shared laboratory tasks and promoting a collaborative environment.

Profile

The ideal candidate will possess the following characteristics:

• A diverse educational background in fields such as engineering, mathematics, computer science, or physics.
• Interests or expertise in areas including Machine Learning, Optimization, Simulation, or Robotics.
• A strong publication record in competitive journals or Computer Science conferences is advantageous but not mandatory, especially for those with practical experience or unconventional career paths.
• Experience with High-Performance Computing (HPC) environments or Software Engineering best practices is a plus.
• Fluency in English and the ability to work collaboratively with diverse, multinational teams.

We encourage all candidates to apply, even if you feel you do not meet every qualification listed above. We are committed to working with selected candidates to develop targeted competencies based on individual needs.

Workplace

Join us in a supportive, innovative, and intellectually stimulating environment. We champion a culture of collaboration and inclusivity, supported by world-class research infrastructure.

We Offer

You can look forward to the following:

• A world-class research infrastructure and excellent working conditions aligned with a supportive culture.
• Opportunities to engage with a diverse and motivated multicultural team within a creative research setting.
• An enriching intellectual environment that integrates insights from top scholars around the globe.
• Support for personalized professional development and mentorship, aiding in building a robust career network.

Equality, Diversity, and Sustainability

ETH Zurich is committed to fostering an inclusive culture that promotes equality of opportunity, values diversity, and nurtures a respectful working and learning environment. Sustainability is fundamental to our values as we endeavor towards a climate-neutral future.

Curious? So Are We!

We encourage you to apply online using the form below. Only applications matching the job profile will be considered.

For further information about our lab, please visit our website. Questions regarding the position can be directed to Mrs. Martina Koch, Administrative Assistant, at Tel: 044 632 45 16 or email: martikoc@ethz.ch.

About ETH Zurich

ETH Zurich is a leading university specializing in science and technology, renowned for its exceptional education, cutting-edge research, and direct transfer of new knowledge to society. With over 30,000 individuals from more than 120 countries, our university fosters independent thinking and inspiration. Located in the heart of Europe, we tackle global challenges collaboratively.