ETH Zurich PhD Scholarship in AI for Materials Modeling (2026) – Fully Funded
Scholarship Description
The Materials Modeling Group, established in February 2026 and led by Prof. Malik Wagih in the Department of Materials at ETH Zurich, invites applications for a fully funded PhD position at the intersection of artificial intelligence, atomistic simulation, and materials science. This is an exceptional opportunity to join one of the group's first doctoral students and help shape its research culture and scientific direction.
ETH Zurich is one of the world's leading universities specialising in science and technology, renowned for excellent education, cutting-edge fundamental research, and direct transfer of new knowledge into society. The research focuses on developing computational methods to accelerate the discovery and design of structural alloys through defect engineering, with particular attention to materials for extreme environments, including fusion energy and space applications.
The PhD project will develop machine-learning methods for atomistic materials modeling, with possible research directions including machine-learned interatomic potentials, physics-informed machine learning, and generative models. The specific research question will be shaped jointly with the successful candidate.
Scholarship Location
The PhD position is based at ETH Zurich, Zurich, Switzerland. ETH Zurich is located in the heart of Europe, forging connections worldwide, and offers a dynamic, international, and interdisciplinary research environment.
Scholarship Deadline
Applications for the PhD position are accepted until 15 July 2026. Applications will be reviewed on a rolling basis until the position is filled.
Application Deadline: 15 July 2026 (rolling review)
Start Date: September 2026 or by mutual agreement
Recommendation: Apply as early as possible — applications are reviewed on a rolling basis and the position may close when a suitable candidate is found.
Host Institution
ETH Zurich – the Swiss Federal Institute of Technology, one of the world's leading universities in science and technology. Over 30,000 people from more than 120 countries find ETH Zurich to be a place that promotes independent thinking and an environment that inspires excellence.
Level and Fields of Study
Level: PhD (Doctoral) – full-time position (100%).
Field: AI for Materials Modeling. The research combines:
- Artificial Intelligence and Machine Learning – developing machine-learned interatomic potentials, physics-informed machine learning, and generative models
- Atomistic Simulation – density functional theory (DFT), molecular dynamics (MD)
- Materials Science – computational methods for structural alloys, defect engineering, materials for extreme environments (fusion energy and space applications)
Target Group
The position is open to highly motivated candidates from all nationalities with a Master's degree (or expected completion before the position begins) in materials science, physics, engineering, computer science, applied mathematics, or a related field. ETH Zurich values diversity and encourages applications from all qualified individuals regardless of gender, ethnicity, or background.
Scholarship Duration & Amount
Duration: Full-time PhD position (typically 3–4 years).
Funding: This is a fully funded position with a competitive salary according to ETH Zurich standards. PhD salaries at ETH Zurich are among the highest in Europe and provide a comfortable living standard in Switzerland.
Benefits include:
- Full funding for the duration of the PhD
- Access to state-of-the-art computational infrastructure
- Interdisciplinary and international research environment
- Opportunity to help shape the group's research culture and scientific direction as one of the first doctoral students
- ETH Zurich's comprehensive support services for international researchers
📊 Summary of Benefits:
Fully funded position with competitive ETH salary + State-of-the-art computational infrastructure + Interdisciplinary & international research environment
Scholarship Eligibility
Essential qualifications:
- A Master's degree (or expected completion before the position begins) in materials science, physics, engineering, computer science, applied mathematics, or a related field.
- Proficiency in programming and scientific computing (e.g., Python, C++, or similar).
- Strong interest in developing or applying artificial intelligence methods to problems in the physical sciences.
- Effective communication skills in English (written and spoken).
Advantageous (but not required):
- Prior experience or coursework in machine learning
- Experience with density functional theory (DFT)
- Experience with molecular dynamics (MD) simulations
✅ Eligible Candidates
- Master's degree in materials science, physics, engineering, computer science, applied mathematics, or related field.
- Proficiency in programming and scientific computing.
- Strong interest in AI/ML for physical sciences.
- Good English communication skills.
- All nationalities welcome.
❌ Ineligible Candidates
- Applicants without a Master's degree (or pending completion).
- Those without programming or scientific computing experience.
- Insufficient English language skills.
- No demonstrated interest in AI/ML or materials modeling.
Application Procedure
- Prepare your application documents – Gather the following materials in PDF format:
- Curriculum Vitae (CV) – detailing your education, research experience, skills, and publications
- Contact information for at least two referees – who can provide academic references (letters may be requested later)
- Academic transcripts in English – from all degrees (unofficial copies are 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
- Submit your application online – Applications are exclusively accepted through the ETH Zurich online application portal. Applications sent via email or postal services will not be considered.
- Application deadline – Submit your application by 15 July 2026. Applications are reviewed on a rolling basis, so early submission is strongly encouraged.
- Application review – Prof. Wagih and the Materials Modeling Group review applications and shortlist candidates.
- Interviews – Shortlisted candidates are invited for interviews (online or in-person).
- Offer and acceptance – The successful candidate receives a formal offer to join the group.
Important notes: Only applications submitted through the ETH Zurich online portal will be considered. If you have questions about the position, contact Prof. Malik Wagih at [email protected] (please note: this address is for inquiries only, not for submitting applications).
Official Website & Application Link
ETH Zurich – PhD Position in AI for Materials Modeling (Official Posting)
ETH Zurich Main Website: https://ethz.ch
Contact for inquiries: Prof. Malik Wagih – [email protected] (inquiries only, no applications)
💡 Final Thoughts and Key Requirements
The ETH Zurich PhD position in AI for Materials Modeling offers a unique opportunity to join a new research group at one of the world's leading universities. As one of the first doctoral students in the Materials Modeling Group, you will have the chance to help shape the group's scientific direction and research culture from the ground up.
Key strategies for a successful application:
- Demonstrate strong programming and scientific computing skills — proficiency in Python, C++, or similar is essential.
- Showcase your interest in machine learning and artificial intelligence applications to physical sciences.
- Highlight any prior experience with density functional theory (DFT), molecular dynamics (MD), or machine-learned interatomic potentials.
- Write a compelling one-page statement about your three proudest achievements — be specific about why they matter and what they reveal about your suitability.
- Ensure your academic transcripts are in English (unofficial copies are accepted).
- Provide contact information for at least two academic referees.
- Submit your application through the ETH Zurich online portal — email or postal submissions will not be considered.
- Apply early — applications are reviewed on a rolling basis and the position may close when a suitable candidate is identified.
Why choose ETH Zurich? ETH Zurich is consistently ranked among the top universities globally for science and technology. The university offers excellent research infrastructure, a vibrant international community, and a commitment to diversity and sustainability. Switzerland offers a high quality of life and is at the heart of Europe's research landscape.
Important reminders: The position is fully funded with a competitive ETH salary. The start date is September 2026 or by mutual agreement. For inquiries about the position, contact Prof. Malik Wagih (inquiries only — applications must be submitted via the portal).
ETH Zurich PhD Scholarship in AI for Materials Modeling 2026 – FAQ
What is the focus of the PhD research?
The PhD project focuses on developing machine-learning methods for atomistic materials modeling, including machine-learned interatomic potentials, physics-informed machine learning, and generative models for materials discovery and design.
What qualifications do I need to apply?
A Master's degree (or expected completion) in materials science, physics, engineering, computer science, applied mathematics, or a related field, with proficiency in programming and scientific computing.
Is this a funded position?
Yes, this is a fully funded PhD position with a competitive salary according to ETH Zurich standards.
What is the application deadline?
The deadline is 15 July 2026. Applications are reviewed on a rolling basis, so early submission is encouraged.
What documents do I need to submit?
CV, contact information for at least two referees, academic transcripts in English, and a one-page statement describing your three proudest achievements and their relevance to the position.
How do I apply?
Submit your application through the ETH Zurich online application portal. Applications sent via email or postal services will not be considered.
Can I contact the group with questions?
Yes, you can contact Prof. Malik Wagih at [email protected] for inquiries about the position (applications must be submitted via the portal).