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Field
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for developing and using systems to phenotype root systems in greenhouse and field settings under the guidance of research mentors. Build skills in root image processing and other data analysis activities using
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progression. Using image-based siRNA screens, we have identified novel regulators of ER-phagy. This project aims to investigate the molecular mechanisms of ER-phagy and how this contributes to cancer
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marine vehicle systems for marine survey. We also explore tools for the visualisation, clustering and classification of extensive marine-based image archives, characterisation of change in multi-year
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interventions. We will enable collaboration between communities, academia, health and care, to drive meaningful change in health equality and social connection. In the process, we will impact research and policy
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apply them to cutting-edge single-cell datasets generated within the lab and from public resources. There is significant scope to shape the project around your interests, including live-cell imaging, flow
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intelligence, including machine learning and computer vision, robotics, and physics-based modelling, the DISC Lab pioneers new methods for monitoring, digitalization, and automation in construction. We
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transcriptomics or proteomics, multiplexed imaging and/or integration of spatial transcriptomics with single-cell RNA-sequencing datasets. Experience from relevant research projects will be considered an advantage
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further develop and implement bioinformatic pipelines. For example, using AI we see opportunities to use the genomic data to train datasets for species identification and delimitation, such as image
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for medical imaging, precision medicine, statistical genomics, graphical models, and the analysis and integration of complex, high-dimensional biomedical data. The fellow will be expected to develop novel
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field high-speed microscopic imaging Experience with control and synchronization of high-speed imaging and lighting systems Experience with image post-processing and data extraction Personal