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heating and cooling, storage, and local electricity grids. A key goal is to translate methodological innovations in deep learning into practical tools for sustainable urban energy systems, supporting
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: Advanced deep learning architectures Mathematical foundations of machine
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. Hu, X. Wei, X. Wu, J. Sun, J. Chen, Y. Huang, J. Chen, A deep learning-enhanced framework for multiphysics joint inversion, Geophysics, 88(1), K13-K26, 2023. https://doi.org/10.1190/geo2021-0589.1 [3
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for enantioselective C-H functionalization chemistry using the latest deep learning tools for protein design. Non-selective photo-chemical methods for C-H heteroarylation have been established using di-aryl ketones as a
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unique atmosphere where there is expertise to dig deep into computational modelling, while remaining connected to the experimental side. This interdisciplinary atmosphere has been a main catalyst for many
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling
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The rapid growth of deep learning has come at an extraordinary environmental and computational cost, yet the standard training paradigm remains remarkably unchanged. Every sample is passed through
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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of novel physics-guided AI algorithms for drug design, integrating physics-based modeling with state-of-the-art deep learning methods. The project will focus on creating a next-generation docking framework