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and regulation of phytohormone transporters—key membrane proteins that control how plants grow and respond to stress. By combining advanced structural mass spectrometry (HDX-MS, native MS) with
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will transition in a second phase to white box approaches that result in interpretable models. For ground truth data, μCT data will be used. A similar approach will be applied using surface roughness
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); novel obfuscations and obfuscation recipes to defeat LLMs and other AI-based reverse engineering tools; the use of AI techniques and LLMs to optimize reverse engineering strategies; modeling techniques
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of teaching and research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we
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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 a doctorate, contains: Are you eager to improve pandemic preparedness through data-driven research? Do you want to work on real-world implementation of AI and epidemiological models in healthcare
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improve the efficiency, maneuverability, and noise performance of drones and other multirotor aircraft, but their deployment requires more advanced modeling and control methods. The PhD will focus
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(Artificial Intelligence and Epidemic Modeling to Prepare Hospitals for the Next Respiratory Pathogen with Pandemic Potential). Project Overview The COVID-19 pandemic exposed critical gaps in our ability
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partially filled containers – is a major challenge in aerospace, transport, and energy systems, where it can compromise stability and safety. The PhD will focus on developing low-order models of sloshing
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are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure