PhD in Machine Learning for Engineering Design

ETH Zürich; Schweiz; Presencial; CHF 42.000 - 52.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

World-class research infrastructure

Diverse, multicultural team

Intellectual environment

Descripción de la vacante

ETH Zurich’s IDEAL Laboratory invites applications for one to two doctoral positions in Machine Learning for Engineering Design. You will work under Prof.

Mark Fuge on AI and ML in engineering design across healthcare, energy, aerospace, and robotics, with opportunities to publish and collaborate with industry and national labs. The role includes teaching support and active participation in a diverse, multinational team.

Formación

• Strong English language skills and ability to work successfully and collaboratively on diverse, multinational teams.
• Background in Machine Learning, Optimization, Simulation or Robotics is desirable.
• Publication record in journals or conferences is a plus, especially for non-traditional career paths.

Responsabilidades

• Conduct individual or collaborative research, write publications, and contribute to code bases.
• Collaborate with industry, academia, and national labs to translate real-world needs into research questions.
• Learn new skills via courses or self-learning and participate in teaching activities as needed.
• Assist with teaching duties for Masters and/or Bachelors thesis students and course support.
• Act as a good lab citizen by helping with shared administrative tasks.

Conocimientos

English proficiency

Team collaboration

Machine Learning

Optimization

Robotics

Educación

Diverse educational backgrounds (engineering, mathematics, CS, physics)

Descripción del empleo

ETH Zurich’s IDEAL Laboratory invites applications for one to two doctoral positions in Machine Learning for Engineering Design. You will work under Prof.

Mark Fuge on AI and ML in engineering design across healthcare, energy, aerospace, and robotics, with opportunities to publish and collaborate with industry and national labs. The role includes teaching support and active participation in a diverse, multinational team.