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and apply machine learning and deep learning models to analyse complex, multi-dimensional datasets, including spatial transcriptomic, proteomic, and single-cell sequencing data. The candidate will
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therapeutic approaches. Advances in proteomic, genomic and transcriptomic technologies offer powerful opportunities to address these challenges. This fully funded studentship forms part of the LifeArc Centre
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biology, neuroscience, extracellular matrix (ECM) biology, spatial transcriptomics, advanced imaging, and immunology, we aim to identify novel therapeutic strategies for patients with glioblastoma
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are interested in using computational methods to understand biology; are fluent in English, written and spoken. Experience with single-cell transcriptomics data analysis and working with high-performance computing
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, molecular and transcriptomic analyses, laser-capture microdissection, and the generation and characterization of lipid nanoparticles. You will work in an interdisciplinary environment combining expertise in
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and experimental models to study metabolic communication in GBM invasion. In this context, spatial transcriptomics and mass spectrometry imaging provide tissue-level maps of tumour–microenvironment
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interdisciplinary training in molecular biology, transcriptomics, bioinformatics, advanced imaging, and 3D cell culture, within a collaborative and well-supported research environment. Supervisors:Dr Susan Armstrong
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consortium (academia, clinics, and industry). Interdisciplinary skillset: from CRISPR/iPSC gene editing and single-cell transcriptomics to microfluidics, proteomics, and translational validation in human
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
leadership, data analysis, and interpretation of results. A substantial component of the role involves the analysis and integration of high-dimensional genomic and transcriptomic datasets, including DNA and
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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