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, we do not know how the shape and flexibility of particles control their preferential sampling of turbulence. The main objective of the thesis is to optimize particle shapes and mechanical properties
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to execute tasks that involve structured data, text, code, and external tools. However, current solutions often rely on generic agents or fixed prompting pipelines that are expensive, difficult to optimize
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learning, with the objective of designing new learning paradigms where synthetic data is generated dynamically to enrich and optimize training datasets. The project focuses on human-centered computer vision
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