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: Kinetic stability data collection for predictive bioprocess modelling of CYP enzymes PhD enrolment: Technical University of Denmark DC4: ML-guided evolution of peroxygenases for selective C-H
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. You are driven by scientific curiosity, enjoy working with complex multi-physics models, and are eager to advance probabilistic methods, machine learning tools, and simulation techniques. If you thrive
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, predictive modelling, and autonomous maintenance solutions. You thrive on scientific discovery, enjoy tackling complex multi-physics problems, and have the drive to explore innovative concepts
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. The position is associated to the ERC Synergy project RECLESS (Recycling versus loss in the marine nitrogen cycle: controls, feedbacks, and the impact of expanding low oxygen regions). RECLESS aims to predict
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seizure detection relies heavily on EEG, but we believe we can do better. NeuroEar aims to use multimodal monitoring to significantly enhance seizure detection and prediction accuracy. This PhD project
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student to work within the ADaM project (Autonomous workflows for Data-driven first-principles Modelling). The project will leverage Large Language Models (LLMs) as active software agents to help automate
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, and ambitious researcher committed to accelerating the green transition by advancing adaptive materials, predictive modelling, and autonomous maintenance solutions. You thrive on scientific discovery
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-pathogen interaction assays; Biofilm models; Proteomics & LC-MS/MS. DC12: Optimizing bioreceptor function in interaction with graphene. Based on modelling/prediction of interaction of receptor molecules
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pathogenesis and host-pathogen interaction assays; Biofilm models; Proteomics & LC-MS/MS. DC12: Optimizing bioreceptor function in interaction with graphene. Based on modelling/prediction of interaction
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to the cyclotron motion of electrons near the plasma center. However, recent models predict that as these waves traverse the plasma edge, they may be influenced by non-linear plasma–wave interactions. Some studies