PhD Position in AI for Materials Modeling — ETH Zürich
NewCHF 73'500 - 111'500
ETH Zürich · Zurich (ZH)
- Location
- Zurich
- Contract
- fixed-term
- Posted
- Yesterday
SalaryCHF 73'500 - 111'500
Role overview
PhD Position in AI for Materials Modeling
100%, Zurich, fixed-term print Drucken
The Materials Modeling Group , established in February 2026 and led by Prof.
- PhD Position in AI for Materials Modeling
- 100%, Zurich, fixed-term print Drucken
Application process
- Malik Wagih in the Department of Materials at ETH Zurich, invites applications for a PhD position at the intersection of artificial intelligence, atomistic simulation, and materials science, starting in September 2026 or by mutual agreement.
- Our group develops computational methods to accelerate the discovery and design of structural alloys through defect engineering, with a particular focus on materials for extreme environments, including fusion energy and space applications.
- Our research combines theory, physics-based simulation, and machine learning. Job description
- The PhD project will develop machine-learning methods for atomistic materials modeling
- Possible research directions include machine-learned interatomic potentials, physics-informed machine learning, and generative models.
- The specific research question will be shaped jointly with the successful candidate
- The successful candidate will join as one of the group’s first doctoral students and will have the opportunity to help shape its research culture and scientific direction. Profile
- A Master's degree, or expected completion before the position begins, in materials science, physics, engineering, computer science, applied mathematics, or a related field
Contacts
- Applications via email or postal services will not be considered. information for at least two referees
- Academic transcripts in English from all degrees (unofficial copies accepted)
- A one-page statement describing the three achievements you are most proud of, why they matter, and what they demonstrate about your suitability for this position.
- Malik Wagih at [email protected] (no applications).
Additional details
- 100%, Zurich, fixed-term
- Our research combines theory, physics-based simulation, and machine learning.
- The successful candidate will join as one of the group’s first doctoral students and will have the opportunity to help shape its research culture and scientific direction.
- Prior experience or coursework in machine learning, density functional theory, or molecular dynamics is advantageous Effective communication skills in English
- Interdisciplinary and international research environment
- Working, teaching and research at ETH Zurich We value diversity and sustainability
- We look forward to receiving your online application with the following documents (in PDF format) by July 15th 2026:
- Contact information for at least two referees
- Applications will be reviewed on a rolling basis until the position is filled.
- cutting-edge fundamental research and direct transfer of new knowledge
Notes and original content
- Job description
- Prior experience or coursework in machine learning, density functional theory, or molecular dynamics is advantageous
- Effective communication skills in English
- chevron_right
- Working, teaching and research at ETH Zurich
- We value diversity and sustainability
- Curriculum vitae
- Applications via email or postal services will not be considered.
- About ETH Zürich
- into society.
