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plant phenotyping, microbiome profiling, predictive modelling and targeted experimental validation to identify the microbial factors that make plants more resilient to disease. Your job You will join the
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Professor Aldo Faisal from Imperial College London involved as international project partner. Research objectives and tasks You will contribute to the development and empirical validation of models
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application! We are looking for a PhD student in Medical Science, AI and Bioinformatics. Your work assignments This project aims to develop AI foundation models for integrative single-cell and multi-omics
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energy piles have been extensively studied, using field tests, physical modelling, and numerical modelling, the behaviour of energy piles under complex thermomechanical loading (e.g. vertical-horizontal
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immunomodulatory compound, you will determine how it reprograms host lipid pathways to boost immunity and eliminate infection. Using lipidomics, zebrafish models and clinical samples, this research will identify
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the microbiome acquired in early life influences immune development and intestinal health? Join an ERC Starting Grant project that combines advanced gut-on-a-chip technology, organoid models and omics approaches
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at Saxion University of Applied Sciences, you will contribute to the development of machine-learning models that connect powder characteristics and process parameters with the properties of the final
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with advanced sports technologies (e.g., metabolic carts, near-infrared spectroscopy, surface electromyography, 3D motion capture, force platforms). Experience with research methods, experimental designs
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interpret experimental and physiological data and contribute to the development of models and predictive approaches for human thermal responses. Communicate scientific results through peer-reviewed
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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high