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attacks Develop and implement ML algorithms to identify vulnerabilities and predict potential threats in supply chain systems Prepare project deliverables and disseminate results through high-quality
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the fundamental aspects of transcriptional control, this project also opens new avenues for the design of climate-resilient crops. Supported by single-cell profiling and predictive artificial intelligence models
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training data. You will unravel the cis-regulatory code controlling context-dependent gene expression and use this information to design synthetic promoters. You will train and evaluate predictive models in
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structures. You will work with both synthetic and experimental 3D ED datasets. Your predictions will enable full structure solution and refinement of materials undergoing gas-phase and electrochemical
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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, and predict their impact on species-specific properties of human neurons. This highly multidisciplinary project will be undertaken in active collaboration with our two labs, at a unique interface of top
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of the TOBI team is to enhance precision cancer management by developing innovative wet-lab and bioinformatic tools for diagnostic, prognostic, and predictive analysis. Prof. Katleen De Preter is the principal