Based at OST, Rapperswil, embedded into the doctoral school of EPFL, and collaborating with SLF. The project: Snow is a highly dynamic porous material mainly made from ice. As the snow structure evolves via so-called snow metamorphism, so evolve macroscopic properties as e.g., radiative properties relevant for surface energy balances and remote sensing. However, the increased understanding of snow processes has not yet found its way into adequate representations at larger scales. One reason is the lack of sufficiently complete metamorphism models that allow for a direct link between ice crystal growth, sublimation, sintering, and bulk properties; another reason is the contrast between empirical approaches of classical snow science versus methods based on fundamental physics. Within a project financed by the Swiss National Science Foundation SNF, we strive to develop a versatile snow metamorphism model that is based on the phase-field methodology and to couple it to radiative transfer models. Comparison with data acquired in paralleling projects running at WSL/SLF and EPFL and analyses using machine learning shall be used to develop upscaling techniques and parametrizations for large scale predictions, e.g., in the context of photovoltaic installations in complex, snow covered terrain. Your responsibilities:Formulate a phase-field model that can predict close to isothermal snow metamorphism. In this case, the process can be interpreted as sintering, whereby intergranular and grain-boundary forces must be adequately considered. Rigid body forces, i.e., movement of individual ice crystals, will present additional challenges. Parametrize the model to represent ice physics as accurately as possible or calibrate parameters using available experimental data.Perform sensitivity analyses to determine dominant driving forces and identify model simplifications while taking strong sensitivities adequately into account.Apply the model to small snow samples obtained from μ-CT and confront modeling results with existing measurement series.Contribute to the overarching project goals by collaborating within the 3-person project team and the partner institutes.Contribute, to a small extent, to teaching and tutoring at OST or EPFL in the context of the doctoral school. Your qualifications:Masters degree in physics, materials science, applied mathematics or equivalentStrong background in and flair for mathematical modelling and numerical simulationInterest in small-scale processes and their impact on large-scale properties, ideally linked to snow or other porous materialsEager to work in a multi-disciplinary context and multi-lingual environment and to collaborate with national and international partnersMotivation to work at the interface between fundamental and applied sciencesWe provide:An independent job that offers both scope for personal initiative and the opportunity to exchange ideas with committed colleaguesA family environment at an applied sciences university with attractive employment conditionsCollaboration opportunities with SLF Davos, EPFL, and École Polytechnique ParisAn attractive workplace on the shore of lake Zurich and in immediate vicinity of the Rapperswil train station and historic (small) townHave we aroused your interest and do you have the desired qualifications? Then send us your complete application documents by using our online tool. For further information, please contact Prof. Dr. Thomas Kaempfer, OST, thomas.kaempfer@ost.ch, +41 79 626 46 37 or, for specific questions on the EPFL doctoral school, Prof. Dr. Michael Lehning, EPFL/SLF, lehning@slf.ch jid3c512bda jit0416a jiy25a