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doctoral candidate who meets the following requirements: A background and strong interest in aluminum alloys, fatigue analysis, and numerical modelling is preferred. Experience with computer aided design and
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and quantitative sustainability assessment methods, including Life Cycle Assessment (LCA), Energy System Analysis (ESA), and socio-economic modeling. The candidate will be expected to contribute
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offered in this context, with the objective of modelling, coding, and field-validating a new mechanistic analysis tool for pavements containing fungal-bound granular layers. The research will focus on urban
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performance utilizing reliable and computationally efficient numerical structural models. To support the condition (state) assessment, you will also explore the use of advanced estimators (e.g., Kalman Filter
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of the nonlinear structural performance utilizing reliable and computationally efficient numerical structural models. To support the condition (state) assessment, you will also explore the use of advanced estimators
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computationally efficient numerical structural models. To support the condition (state) assessment, the project will also explore the use of advanced estimators (e.g., Kalman Filter) or Machine Learning models
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experience with: Signal processing Experimental design and data analysis Furthermore, the successful candidate is expected to: Have excellent knowledge of English (written and spoken). Have high self