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key research questions that crosscut the themes of statistics, graphical models, causal inference, active learning, spatial modeling, and deep generative models. Execute multiple projects that will
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wavelengths enables the derivation of the fractional surface coverage of coherent rock. Thermal modeling can also reveal spatial variability in the density of the fine-grained regolith. These physical
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analytical or computational methods (e.g., remote sensing, spatial analysis, systems or integrated assessment modelling) applied to sustainability. Candidates from other methodological areas with clear
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network discovery and individualized circuit targeting, multimodal concurrent brain stimulation-recording, and computational modeling. We bridge invasive approaches, including intracranial electrical
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Data Analytics and Modelling Infrastructure (ÉireOcean-TWIN) For an information package including full details of the post, selection criteria and application process see https://ore.ucc.ie
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on developing probabilistic latent-variable methods for large and structured biological data, with applications in genomics, spatial transcriptomics, and fluorescence imaging. High-dimensional and structured
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resistance. This work will integrate spatial transcriptomics, advanced co-culture organoid assays, and in vivo models to decode the mechanisms underlying CAF-driven CRC evolution. Access to single cell RNA
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. Description: The transition in the Arctic from multi-year ice to first year ice raises the urgency of process understanding and modeling of sea ice formation/melt processes, including the interaction with
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and damaging storms, and cascading risks such as bark-beetle outbreaks. Forest owners and regional authorities need spatially detailed, timely information on where climate stress is emerging, and which
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stress affects specific cell types in the nervous system and the gut, using human pluripotent stem cell (hPSC)-derived models of the enteric nervous system. Our work sits at the intersection of stem cell