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will be developed. Finally, the research will develop efficient algorithms and test them on realistic networks and using real data from energy and public transport operators. The Doctoral student is also
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involves developing state-of-the-art methods for image segmentation, detection, classification, predictive modelling, and image enhancement. We aim to build more trustworthy and robust AI models that can
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within the Faculty. Along with the disciplinary approach a very ambitious interdisciplinary research culture has been developed. The faculty's research and teaching focuses on social, economic, political
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4 fully funded PhD student positions in the computational, mathematical & experimental plant science
. More than 30 research groups study regulatory networks controlling fundamental traits such as reproductive development, organ geometry and growth, innate immunity and microbiome effects on plant performance
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to the recruitment and promotion of female leaders and their career development.