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to facilitate a rapid and efficient exchange among experimental and computational groups and Devise an approach in invertible predictive modelling that links semiconductor properties to the composition of lead
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nano-structures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA nanoconstructs. The primary goal is to build an AI
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learning (ML) methods—including surrogate modeling, feature extraction, and inverse design algorithms Generate synthetic microstructures (based on the open source OptiMic software) Perform descriptor
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interdisciplinarity and transfer of science to society. As a modern employer, it offers attractive working conditions to all employees in teaching, research, technology and administration. The goal is to promote and
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plant genetic mechanisms that coordinate mycorrhizal interactions with plant P and water status, root system development, and soil microbial communities. Using maize and rice as models, we will: 1
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plant genetic mechanisms that coordinate mycorrhizal interactions with plant P and water status, root system development, and soil microbial communities. Using maize and rice as models, we will: Determine
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Description Water can move in two interconnected realms: the fast, visible rivers at the surface and the slower, pressure-driven flow within substrates. Today, engineers can model each realm
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Description The majority of hydrological models rely heavily on the principle of mass balance, often represented through Ordinary Differential Equations (ODEs). These models encapsulate
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of the Research School will be anchored in a robust thesis advisory committee (TAC) model, designed to provide comprehensive support and guidance to PhD students throughout their research journey. Each student will
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to investigate mechanical properties under application-relevant conditions Microstructural characterization using advanced optical and electron microscopy techniques Analysis and correlation of mechanical behavior