PhD Student in Computational Snow Physics / PhD Studentess in Computational Snow Physics

PhD Student in Computational Snow Physics (100%)

OST – Eastern Switzerland University of Applied Sciences, serves the six cantons of Eastern Switzerland and the Principality of Liechtenstein. We are an innovative and dynamic university dedicated to making significant contributions to the economic and social development of the region. With approximately 3,800 students across six schools, 1,500 professionals engaged in executive education, and over 1,000 active research projects, we proudly stand as the educational hub of Eastern Switzerland.

EPFL – École Polytechnique Fédérale de Lausanne, is recognized as Europe’s most cosmopolitan technical university. Collaborating with a diverse network of partners—including other academic institutions, industries, and political entities—EPFL aims to create a meaningful impact on society.

WSL Institute for Snow and Avalanche Research SLF, located in Davos, focuses on studying snow, atmospheric phenomena, natural hazards, permafrost, and alpine ecological systems.

We are seeking an enthusiastic PhD Student in Computational Snow Physics based at OST, Rapperswil, integrated within the doctoral school of EPFL and collaborating closely with SLF.

The Project

Snow, a highly dynamic porous material primarily composed of ice, undergoes structural changes known as snow metamorphism. This process influences macroscopic properties, such as radiative characteristics that are crucial for surface energy balances and remote sensing applications. However, the increased understanding of snow processes has not been effectively applied to larger scales. One challenge is the lack of comprehensive metamorphism models that connect ice crystal growth, sublimation, sintering, and bulk properties. Additionally, there is a disparity between empirical approaches of traditional snow science and methodologies grounded in fundamental physics.

Funded by the Swiss National Science Foundation (SNF), our objective is to develop a versatile snow metamorphism model utilizing phase-field methodology, which will be coupled with radiative transfer models. We will compare our findings with data from parallel projects at WSL/SLF and EPFL and utilize machine learning analyses to develop upscaling techniques and parameterizations for large-scale predictions, such as those needed for photovoltaic installations in complex, snow-covered terrains.

Your Responsibilities

• Formulate a phase-field model to predict near-isothermal snow metamorphism, interpreting the process as sintering while accounting for intergranular and grain-boundary forces.
• Parametrize the model to accurately represent ice physics or calibrate parameters using available experimental data.
• Conduct sensitivity analyses to identify dominant driving forces and explore model simplifications while addressing significant sensitivities.
• Apply the model to small snow samples obtained from μ-CT, comparing modeling results with existing measurement series.
• Collaborate within the three-person project team and partner institutes to achieve overarching project goals.
• Contribute minimally to teaching and tutoring at OST or EPFL as part of the doctoral school.

Your Qualifications

• Master's degree in physics, materials science, applied mathematics, or a related field.
• Strong proficiency in mathematical modeling and numerical simulation.
• Interest in small-scale processes and their implications for large-scale properties, preferably related to snow or other porous materials.
• Enthusiasm for working in a multidisciplinary and multilingual environment, collaborating with national and international partners.
• Motivation to bridge the gap between fundamental and applied sciences.

We Provide

• An independent role that encourages personal initiative and the opportunity for intellectual exchange with dedicated colleagues.
• A supportive environment at an applied sciences university with attractive employment conditions.
• Collaboration opportunities with SLF Davos, EPFL, and École Polytechnique Paris.
• An appealing workplace on the shores of Lake Zurich, conveniently located near Rapperswil train station and the historic town.

If you are intrigued by this opportunity and possess the desired qualifications, please apply online using the form below. Only applications matching the job profile will be considered.

For further information, please contact:

• Prof. Dr. Thomas Kaempfer, OST: Show e-mail, Show phone
• Prof. Dr. Michael Lehning, EPFL/SLF: Show e-mail