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machine learning (ML) approaches offer a powerful framework for modeling complex catalytic materials with near ab initio accuracy while enabling simulations at significantly larger spatial and temporal
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Research Associate - Livestock Spatial Modeler The College of Agriculture and Life Sciences (CALS) is a pioneer of purpose-driven science and Cornell University’s second largest college. We work
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to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large
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colleagues on multi‑omics data integration and analysis. You will also work with AI experts to help implement predictive models that improve guide design and functional genomics workflows. You will join an
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colleagues on multi‑omics data integration and analysis. You will also work with AI experts to help implement predictive models that improve guide design and functional genomics workflows. You will join an
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the Collaborative Doctoral Partnerships programme, training researchers at the science-policy interface. Where to apply Website https://jobs.unibas.ch/offene-stellen/phd-position-ai-driven-pathways-to-health
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tissue collection infrastructure, generate foundational single-cell and spatial omics datasets, and develop patient-tissue glioma organoid (PTGO) models to test immunotherapy strategies. The ultimate goal
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the production of spatially granular and engineering driven representations of model results. Experience working across disciplines in multi-institution and multi-stakeholder collaborations is desirable
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for therapeutic intervention. This PhD project will leverage large-scale single-cell RNA-seq and spatial transcriptomics datasets from infection biology to develop models, including transformer-/graph-based models
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Vacancies PhD Position on Fundamental Aspects of the NaAlCl Battery Key takeaways As part of the ~30 Mio€ ‘SLDBatt’ project, the largest R&D project into battery technology for long-term storage