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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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Natural Language Processing (NLP) in the areas of culturally aware NLP or multilingual conversational NLP, and integration of such methods to support language technology in multiple languages
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sequencing (NGS), and bioinformatics analysis is highly desirable. You will join a multidisciplinary team of approximately 15 experienced chemists, chemical biologists, and molecular/cell biologists based in
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transposable element biology. They should be able to develop and apply at scale bioinformatic tools that identify and classify transposable elements, and the variation they create. Solid experience in
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techniques including confocal microscopy, bioinformatics and infection assays in CL2 facilities. Main duties: Generate, maintain and characterise organoid and macrophage culture systems. Design, implementation
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or sensor arrays. Experience generating, processing and analysing large material property datasets including correlating between multiple techniques, or developing computational reconstruction techniques
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metrics during both standard operation (primarily governed by system reliability) and extreme events (primarily governed by robustness and restoration). This will be achieved by building on previous
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Nanopore sequencing, ChIP-seq, and Hi-C, to probe plant genomes and centromeres. The project will involve both wet-lab based functional genomics approaches, together with dry-lab based bioinformatics
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Nanopore sequencing, ChIP-seq, and Hi-C, to probe plant genomes and centromeres. The project will involve both wet-lab based functional genomics approaches, together with dry-lab based bioinformatics