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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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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 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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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
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analysis and statistical modeling. Experience working with large, complex, and multi-dimensional datasets. Experience with spatial analysis and geospatial data integration, including use of GIS tools (e.g
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. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models