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of a doctorate, contains: Are you eager to improve pandemic preparedness through data-driven research? Do you want to work on real-world implementation of AI and epidemiological models in healthcare
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to detect and respond to emerging respiratory viruses. ANTICIPATE aims to strengthen pandemic preparedness by developing AI-driven tools and epidemiological models to (1) detect novel pathogens early through
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mobility of migrants shape local populations? Developing a spatial microsimulation model of population dynamics with application in infectious disease modelling (DynaMIGs)”. DynaMIGs is a four-year
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to the collected dataset. Deep learning will focus on physics-based features developed earlier. Convolutional layers will be used to extract spatial patterns, while LSTM layers will capture temporal aspects across
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spatial distributions of active phases across multiple length scales. The PhD student will collaborate with international partners to study the evolution of crystalline and amorphous domains in the hybrid
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acids in both tissue and liquid biopsy samples will be investigated. Examples of techniques that will be used in this PhD project include DNA/RNA isolation, DNA/RNA sequencing, spatial transcriptomics
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-driven approaches to health, society, and policy. BISI combines expertise in epidemiology, biostatistics, health economics, and machine learning to tackle complex societal challenges. BISI is actively
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devices that incorporate strategic markings, to improve the spatial resolution of 5D ED experiments (which involve both 4D-STEM and 3D ED). You will code the necessary tracking software for your developed
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will employ advanced in vivo models and spatial technologies to dissect the roles of tissue-resident macrophages and infiltrating immune cells along the periphery–immune–brain axis. About us The research
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drive neuroinflammation in synucleinopathies and other neurodegenerative diseases. The candidate will employ advanced in vivo models and spatial technologies to dissect the roles of tissue-resident