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in thermodynamics, optimization, and control theory. Strong understanding of mathematical modeling, numerical optimization, and/or model predictive control (MPC). Experience working with large-scale
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powerful, modern analytical techniques including chemical proteomics and metabolomics. They will have access to advanced synthesis facilities, as well as biological models, such as macrophages and organoids
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, the PhD researcher will develop physiological-model-based artificial intelligence technologies to assess patients’ recovery process, detect or even predict the occurrence of clinical adverse events like
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, classical ecological theories and methods to mathematically model species interactions networks and communities across spatial scales. As part of the project, the student will extend these methods and make
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will be trained in a variety of powerful, modern analytical techniques including chemical proteomics and metabolomics. They will have access to advanced synthesis facilities, as well as biological models
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to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model development using Python and/or other programming languages
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capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives, including large-scale
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Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
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interdisciplinary character. The Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering
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powerful, modern analytical techniques and have access to advanced synthesis facilities, as well as biological models, such as macrophages and organoids, to enable the rapid translation of this research