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sensing, high-resolution plume modelling (MicroHH), and atmospheric chemistry transport models (LOTOS-EUROS, ECHAM-HAM). The focus will be on better characterizing fire emissions, smoke plume injection
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decision support tools. These mathematical models help battery owners make strategic decisions, such as when to charge and discharge or on which electricity markets to focus. In this PhD trajectory, we
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batteries enter the power system, requires state-of-the-art decision support tools. These mathematical models help battery owners make strategic decisions, such as when to charge and discharge or on which
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that the developed methods are robust, adaptable, and grounded in real-world practice. You will apply advanced techniques such as agent-based modelling, quantitative resilience assessment, and risk analysis to
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income) and related environmental impacts (for example changes in soil carbon and/or reduced nitrogen losses). Research methods will include statistical analyses, modelling and potentially farm interviews
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-based modelling, quantitative resilience assessment, and risk analysis to simulate and optimise resilience strategies. The framework will be tested and refined through pilot studies in collaboration with
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structural assemblies to nanomechanical resonators. In the second direction, you will explore the geometric design of nonlinear systems. Using nonlinear reduced order modelling (ROM) integrated with
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van Erven. This is what you will do AI and machine learning models keep getting better, but how they make their decisions often remains unclear, because these depend on many incomprehensible model
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the second direction, you will explore the geometric design of nonlinear systems. Using nonlinear reduced order modelling (ROM) integrated with optimization algorithms, you will design structures
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, supervised by Dr. Tim van Erven. This is what you will do AI and machine learning models keep getting better, but how they make their decisions often remains unclear, because these depend on many