Postdoc: AI-Driven Engineering Design

ETH Zurich; Zürich; Hybrid; CHF 110,000 - 140,000; Full time

Benefits offered by this job

Home office option

Professional development support

Job summary

ETH Zurich’s IDEAL Lab invites applications for a post-doctoral position in Machine Learning for Engineering Design. The role focuses on AI-guided design, inverse design, and optimization across healthcare, energy, aerospace, and robotics, with opportunities to shape research infrastructure and collaborate with Ph.D.

students and staff. The successful candidate will lead algorithms, coordinate projects, and contribute to world-class publications while benefiting from ETH’s strong support for

Qualifications

• PhD in Mechanical Engineering, Computer Science, Applied Mathematics, Robotics, or related fields with an excellent track record in archival journals and conferences.
• Strong English language skills and ability to collaborate in multinational teams.
• Preferred familiarity with ML or HPC tooling (e.g., PyTorch, JAX) and packaging codes for deployment on distributed servers.
• Experience with formal verification or software analysis is desirable.

Responsibilities

• Develop or analyze novel algorithms for engineering design applications (e.g., inverse design, generative modeling, robotics).
• Collaborate with industry, academia, and national labs to translate needs into scientific questions.
• Deploy simulation or algorithm pipelines on HPC infrastructure.
• Coordinate development efforts of team members and contribute to lab infrastructure.
• Assist in teaching efforts and supervise students when needed.
• Contribute to dissemination through publications and conferences.

Skills

Machine Learning

Robotics

Computational Simulations

Engineering Problems

High-Performance Computing

Software Engineering

Education

PhD required

Tools

PyTorch

JAX

Docker

Singularity

HPC clusters

Job description

ETH Zurich’s IDEAL Lab invites applications for a post-doctoral position in Machine Learning for Engineering Design. The role focuses on AI-guided design, inverse design, and optimization across healthcare, energy, aerospace, and robotics, with opportunities to shape research infrastructure and collaborate with Ph.D.

students and staff. The successful candidate will lead algorithms, coordinate projects, and contribute to world-class publications while benefiting from ETH’s strong support for