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Field
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PhD Scholarship Develop multimodal machine learning models to predict glioblastoma treatment outcomes using imaging and clinical data. Work with real-world data from John Hunter Hospital in a
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the University of Warwick. Project outline: Modelling light-driven processes and charge transfer across molecule-metal interfaces is instrumental for the development of next-generation molecular optoelectronic
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) About the Project Unravelling the outcomes of cell–cell interactions is fundamental to understanding biological processes. The ability to visualise and track these interactions in vivo greatly enhances
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to establish the foundation for functional retinal imaging based on the dynamics of molecular processes [Progress in Retinal and Eye Research 93, 101170 (2023); The Journal of Clinical Investigation
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organizational levels of the brain – from molecular and cellular processes to complex neuronal networks and behavior. In association with the SFB 1436, Neural Resources of Cognition (supported by the German
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experiments using MEA electrophysiology, live-cell imaging, and related techniques. You will study neuronal failure and recovery after metabolic stress in rodent and human iPSC-derived cultures, and evaluate
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expression underlies nearly every biological process in eukaryotes. It is facilitated through transcription factors (TFs), which bind to DNA and influence mRNA production at target genes. Organism-wide changes
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digital signal and image processing, IoT, cyber security, deep learning, and software systems. Applications in healthcare, multimedia, and sustainable urban environments are encouraged. School
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protocols and have affinity with medical topics. You have knowledge of CT dosimetry and radiation physics. You have good experimental skills and experience with image processing. You have some knowledge in
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 1 day ago
interacting fibers producing visually appealing images. However, these simulators remain limited to fibers with small natural curvature, making them unable to retrieve the rich phenomenology observed for highly