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of the characterisation techniques used in the field obtain average properties of what in reality is an ensemble of molecules. The aim of this project is to study the influence of molecular disorder on the light emission
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the ability to learn from experimental data and make meaningful predictions, taking AlphaFold and its highly accurate protein structure prediction as an example. However, the training of powerful AI tools
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: Develop innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry
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(SMI) techniques, supported by cell biology. This PhD project will involve characterizing the molecular mechanism of BIR in unprecedented details using purified proteins, ensemble biochemistry and SMI
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. However, the impacts of measures aimed at improving air quality are difficult to predict. One reason for this is that ozone formation depends on the concentration of precursor substances such as nitrogen
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industry and academia, including experts on system services, converter control, flow propagation and lidar-based predictions. Among others, your tasks will comprise: Development of control algorithms