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directions include: ● Generative models of cell–cell communication . Move beyond descriptive ligand–receptor analysis to models that predict and help understand how cells react to signaling cues. ● Joint
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of this project is to use modern multiomic spatial methods (in which our group has extensive expertise14) together with deep learning (for efficient representation and cross-modal learning) to discover the
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modalities, spatial scales, and diverse populations. Position Highlights Work with cutting-edge multimodal concurrent stimulation-recording datasets spanning iES, TMS, iEEG, single-unit, and fMRI. Study causal
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communication. Move beyond descriptive ligand–receptor analysis to models that predict and help understand how cells react to signaling cues. ● Joint models of regulation and dynamics. Flow- and diffusion-based
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models that includes breeding colony management and genotyping. Performs advanced 3D and spatial imaging (confocal, LSFM, Xenium spatial transcriptomics) and associated computational image analysis
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on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and Data Science, Safety and
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Institute of Neuroscience and physiology, Sahlgrenska Academy, university of Gothenburg | Sweden | 23 days ago
insufficiently established, and emerging modalities capturing processes upstream of atrophy require validation. This PhD project uses multimodal neuroimaging to decipher early neurodegenerative disease across
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histopathology and clinical information to learn robust cross-modal representations for diagnostic prediction. It pursues two integrated objectives: (i) to develop generative and explainable AI approaches
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pathology, whole slide image analysis, or quantitative microscopy. Experience integrating multi-modal datasets, including genomics, transcriptomics, spatial transcriptomics, proteomics, metabolomics, imaging
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scientific initiative focused on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and