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with expertise in bioinformatics, machine learning, data integration & harmonization, natural language processing including large language models, imaging informatics, and pathology informatics are
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Programme is a scientific visitor scheme designed to provide early-career students/researchers (prior to embarking on a PhD) with a passion for technology and tool development an opportunity to gain hands
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using hybrid models combining mechanistic, GenAI, and machine learning approaches. You’ll contribute to building disease-specific Digital Twins using large-scale single-cell multi-omics datasets
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UK universities through Japan-UK ASPIRE program, covering synthetic biology, machine learning, and quantum computing, will be available. We promote equal opportunities, diversity, and inclusion
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Devices (QCD) group at the Department of Applied Physics. In this position you have a chance to make history by demonstrating some of the first experiments of the future quantum-computer technology that is
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to the success of the whole institution. At the Faculty of Chemistry and Food Chemistry, the Chair of Theoretical Chemistry offers a position as Research Associate / PhD Student (m/f/x) (subject to personal
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research to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine
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maintain pipelines for the analysis of high-throughput sequencing data, including RNA-seq, ChIP-seq, ATAC-seq, and single-cell and spatial omics. Integrate machine learning and large language models (LLMs
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Associate Professor or DTU Tenure Track Assistant Professor (junior group leader) in High-through...
) to in-field testing of up to 800 strains. The scale and standardized approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed
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Associate Professor or DTU Tenure Track Assistant Professor (junior group leader) in Fermentation...
) to in-field testing of up to 800 strains. The scale and standardized approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed