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for existing medications, a strategy that can significantly reduce the time and cost required to bring a drug to market. The project will use AI models such as CycleGANs, that by learning from complex spatial
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@cytiva.com . Join our winning team today. Together, we’ll accelerate the real-life impact of tomorrow’s science and technology. We partner with customers across the globe to help them solve their most complex
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and computational modeling to understand complex biological processes. Experience in statistical modeling, machine learning, or analysis of spatial or high-dimensional biological data is considered
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of small cryptic plasmids in the development and spread of antibiotic resistance, and ii) Use machine learning tools to examine the complex interplay between bacterial hosts, various plasmids and resistance
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. The project revolves around developing Traident – a new method to resolve the species origins and compositions of complex RNA sequence data. This will extend Kraken2 with analyses of ribosomal RNA and microRNA
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Adverse Effects.” This project aims to unravel the complex relationships between medications and their effects on biological systems, and to identify key determinants of drug efficacy and adverse reactions