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, modelling, and AI to turn scientific research into real-world impact. You’ll join an open, supportive environment that fosters learning and professional growth. Job requirements Must haves: Master’s degree in
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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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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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-edge infrastructures, and emerging AI-driven user applications. Key research directions include: Modeling and profiling of emerging AI-based workloads and data-intensive applications in mobile networks
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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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, 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
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, employees, IT infrastructure, specialized training). Second, they may require the use of quantitative models, data analysis, and algorithms, but these applications must also safeguard the data privacy and non
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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