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from massive datasets. Their ability to capture transferable knowledge offers a unique opportunity to rethink the modeling of physical interactions. The central idea of this PhD is that a model trained
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Filters and particle filters. Knowledge of battery degradation, ageing, and state estimation (SOC, SOH, SOP), including diagnostics and prognostics. Familiarity with reduced-order electrochemical models and
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should help identify pathways and policies that can contribute to desirable long-term societal outcomes. The research is expected to advance both methodological knowledge in transport modelling and
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: Experimental skills in the mechanical characterization of fiber reinforced composites or polymers; experience with fatigue testing is desired. Theoretical knowledge and skills in the modelling of (failure
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mathematical modelling and the development of FEM models of transformers and inductors; knowledge of Ansys is an advantage; • publication record in peer-reviewed journals and at professional or scientific
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Candidates should demonstrate experience and/or knowledge in one or more of the following areas: Numerical modelling of materials and structures using the Finite Element Method (FEM). Simulation of damage and
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at https://biffilab.wordpress.com Pancreatic ductal adenocarcinoma (PDAC) remains a formidable clinical challenge. A major recent advance has been the development of KRAS inhibitors, which have shown
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and the various components of the tumour microenvironment. The research will primarily be conducted using patient-derived glioblastoma models and will combine approaches from cell and molecular biology
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these exclusively via our job portal. Applications by e-mail and by post will not be considered. Where to apply Website https://academicpositions.com/ad/empa/2026/phd-position-multi-scale-modelling-a… Requirements
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» Cognitive scienceYears of Research ExperienceNone Research FieldPsychological sciences » PsychologyYears of Research ExperienceNone Additional Information Website for additional job details https