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This postdoc position is designed for a specialist in the fabrication and development of large-scale perovskite solar cells and modules. For this position, we are looking for a candidate with an
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are looking for someone with proven experience in semiconductor device fabrication and characterization. Responsibilities Development and optimization of silicon heterojunction solar cells at different levels
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on the development and implementation of new workflows for the mineralogical and geochemical characterization of ore materials, using combined µXRF-mapping, SEM-based automated mineralogy, and laser ablation ICP-MS
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to integrate advanced sensing, electrical, thermal, and mechanical diagnostics to capture aging, degradation, and damage evolution under realistic service conditions. Emphasis is placed on non-destructive, real
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for characterization of interfaces in non-conventional configurations, including ultra-low loading and/or curved configurations. Contribute to the development of new interphase concepts for the toughening or challenging
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operation and failure conditions, including thermal runaway initiation and propagation. · Analyze coupled failure mechanisms involving heat generation, gas evolution, internal shorting, and structural
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on the development of new methods integrating a variety of data types (remote sensing, geology, geophysics, geochemistry) for geological modelling and advanced exploration targeting of mineral deposits
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. Analyze coupled failure mechanisms involving heat generation, gas evolution, internal shorting, and structural degradation, and connect them to cell- and pack-level safety performance. Design model-based
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family of printable high-gauge factor wireless sensors by building and extending our related background intellectual property. Responsibilities : Collaborate with the development of a new family of RFID
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containment. The prohibitively high computational cost of such simulations necessitates the development of efficient and robust surrogate models for general GCS modeling tasks, especially when inverse modeling