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, including data from ELISA, PNA, ELISPOT, flow cytometry, B and T cell receptor sequencing, and transcriptomics. You will develop a reproducible informatics and machine learning pipeline to process large
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and realign how we measure and model populations by infusing new types of data, methods and unconventional approaches to tackle the most challenging demographic problems of our time. We are looking
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with large SQL databases Experience with SSRS, Power BI or similar reporting tools Ability to lead and supervise others Experience of managing and developing data systems in an FE or other educational
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in these elements leads to common and rare disease. You will work with large scale genome sequencing datasets (e.g. UK BioBank, 100,000 Genomes Project, gnomAD) and RNA-Seq data, adapting and applying
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models and rapid-response tools and emulators. All work is theoretical/computer based and no real-world deployment of SRM techniques is included. Focus will be on understanding climate thresholds that may
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computationally demanding research. Join us and: Provide HPC & Cloud facilities and support the people who use them to: Run large- or small-scale simulations, data analyses and machine learning workloads Have the
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successful collaboration on the Common Data Environment (CDE) and support successful processing of information through workflows. Push the boundaries of analysing, interpreting and presenting large quantities
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access to expertly curated, longitudinal, multimodal cancer datasets and AI models for researchers in industry and academic institutions. The data and the development of AI within the platform, in
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? Are AI and big data the future of finance? King’s Business School (KBS) contributes towards answering these questions, changing the way business works whilst tackling the world’s major challenges
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? Are AI and big data the future of finance? King’s Business School (KBS) contributes towards answering these questions, changing the way business works whilst tackling the world’s major challenges