Doctoral Position in Mechanics of Frictional Particle Suspensions
Investigate how microscopic frictional interactions govern the macroscopic behavior of dense particle suspensions.
Best for:Best for graduate students in mechanics or physics with a strong background in scientific computing and numerical modeling.
Overview
The Professorship of Solid Mechanics at ETH Zurich invites applications for a doctoral position focused on the mechanics of frictional particle suspensions. The successful candidate will conduct computational and theoretical investigations to link particle-scale friction with macroscopic rheological flow responses. Working within an interdisciplinary and international research team, the student will employ particle-based simulation methods, such as coarse-grained molecular dynamics, and collaborate closely with experimental partners. The project offers a stimulating environment for scientific growth aimed at developing predictive tools for complex material failure.
What you'll do
- Conduct computational and theoretical investigations into how particle-scale friction governs the macroscopic flow response of concentrated suspensions.
- Connect particle-scale mechanics, geometry, and frictional interactions with collective suspension behavior using physics-based models.
- Implement and execute particle-based simulation methods, including coarse-grained molecular dynamics.
- Perform rigorous verification and validation of computational results using reference datasets provided by collaborators.
- Analyze simulation findings to uncover the physical mechanisms controlling suspension dynamics and assist in interpreting experimental observations.
Requirements
Degree required: MSc degree in mechanics, physics, engineering, material science, or a related discipline
Degree offered: PhD
Language: English; fluent oral and written proficiency
Instruction: English
- Background in mechanics, applied physics, computational mechanics, or scientific computing
- Experience in implementing scientific code and validating computational results
- Prior programming experience in Python
- Familiarity with version control systems
- Strong interest in quantitative reasoning, modeling, and interdisciplinary collaboration
Funding & terms
How to apply
Submit your application exclusively through the online application portal, ensuring all requested documents are attached. Applications sent via email or postal services will not be considered.
- CV
- Academic transcript
- Project idea statement
- 2 reference letters
Contact
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