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measurements and process-based modelling to identify the mechanisms linking vegetation, soil microorganisms and ecosystem carbon cycling. The project spans laboratory, field and ecosystem scales and combines
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holographic information using natural and spatially incoherent light sources. However, the image quality of such systems is still limited by inaccurate models of incoherent light propagation and by the complex
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Engineering, Bioinformatics, Statistics, Applied Mathematics, Physics, or a closely related STEM field. Demonstrated experience developing AI and machine learning models for biomedical applications. Job
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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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complex contexts through statistical models, machine learning (ML) methods, and artificial intelligence (AI). This includes working with performance, scalability, resilience regarding platform architectures
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provide faculty-level scientific continuity, lead experimental strategy, coordinate studies across collaborators and core facilities, troubleshoot complex leukemia models, interpret integrated datasets, and
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in the elderly population, and its pathological mechanisms are complex and not fully understood. In human patients, the elevated systemic levels of five factor H-related proteins (FHRs1-5) have been
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of the project is to develop statistical theory, methodology, and computational methods for such complex data problems, with a particular focus on models for latent variables and their connections to modern
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, including situations where some modalities are incomplete or unavailable. Exploring foundation-model and self-supervised learning approaches for extracting transferable representations from large-scale forest
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transcriptomics and fluorescence imaging data to improve our understanding of complex biological systems. The project is particularly suited to a candidate interested in probabilistic modelling, latent-variable