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description Specifically, this project combines high-throughput experimentation, synthesis of model catalysts, operando characterization, and molecular modelling to identify novel catalyst families and develop
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with large language models (LLMs). The successful candidate will investigate both theoretical aspects – such as understanding the mechanisms and limitations of reasoning in modern LLMs – and practical
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. Project background The position is associated to a project on phase-field modeling of fracture. The PhD project aims at developing cutting edge models for the fracture behavior of quasi-brittle materials
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publications. Desired: Experience in nanopore and/or other single-molecule experiments and their interpretation Coding skills for advanced data analysis, machine learning, kinetic modeling, etc. Nanofabrication
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-molecule techniques. Coding skills for data analysis, pattern recognition, machine learning, kinetic modeling, etc. Advanced optics, biochemical wetlab, and/or bioengineering experience. Required: MSc degree
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their subsequent simultaneous analysis. This project aims at overcoming these challenges to reliably measure atmospheric levels of PFASs and model their respective emission strengths in Switzerland
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2026. The UNFoLD lab specialises in the experimental measurements, analysis, and modelling of unsteady vortex-dominated flow phenomena, with applications in bio-inspired propulsion, wind turbine rotor