PhD Student in Machine Learning for Engineering Design / PhD Studentess in Machine Learning for Engineering Design

PhD Position in Machine Learning for Engineering Design

100%, Zurich, fixed-term

Project Background

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 encompasses the study of Artificial Intelligence and Machine Learning in the context of Engineering Design problems in various domains such as healthcare, power generation, aerospace, and robotics.

This search is broad and not tied to a specific project, allowing us to prioritize scientific excellence and fit with the laboratory. Current research interests 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
• 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 shared code bases.
• Collaborating 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 through courses, educational offerings, or self-learning.
• Assisting with the teaching mission of the laboratory, including mentoring Master's and Bachelor's thesis students and providing course assistance as needed.
• Contributing positively to the lab environment by assisting in various shared administrative tasks.

Profile

The ideal candidate will possess the following characteristics:

• Diverse educational backgrounds are welcome, including engineering, mathematics, computer science, and physics.
• Interests or expertise in areas such as Machine Learning, Optimization, Simulation, or Robotics.
• A strong publication record in competitive journals or computer science conference venues is advantageous but not essential, especially for candidates with practical experience or non-traditional career paths.
• Experience with High-Performance Computing (HPC) or Software Engineering best practices is a plus but not required.
• Strong English language skills and the ability to work collaboratively in diverse, multinational teams.

We encourage candidates to apply even if they do not meet every criterion listed above, particularly those who may not have had access to certain development opportunities. Selected candidates will receive tailored support to develop essential competencies.

Workplace

ETH Zurich provides an enriching work environment, fostering collaboration and innovative research among a diverse and motivated team.

We Offer

You can look forward to:

• World-class research infrastructure and excellent working conditions supported by a collaborative culture.
• Opportunities to work within a diverse, multicultural team in a dynamic research environment.
• A rich intellectual setting within the lab and university, interacting with top scholars from around the globe.
• Support for personalized professional development and mentorship, fostering a strong network for your future career.

We Value Diversity and Sustainability

In line with our values, ETH Zurich fosters an inclusive culture, promoting equality of opportunity and valuing diversity. We nurture a working and learning environment that respects the rights and dignity of all staff and students. Sustainability is a core value, and we are committed to working towards a climate-neutral future.

Curious? So Are We.

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, Adm. Assistant, at Tel 044 632 45 16 or via email at martikoc@ethz.ch (no applications).

About ETH Zurich

ETH Zurich is a premier university renowned for its specialization in science and technology. With over 30,000 individuals from more than 120 countries, we promote independent thinking and foster an inspiring environment. Located in the heart of Europe, we connect globally to tackle pressing challenges of today and tomorrow.