304 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" research jobs in Sweden
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome
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. The position includes the opportunity for three weeks of training in higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create
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of training in higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity of further development. Your work duties will
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machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome, etc.) development of predictive models and digital decision-support
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highly interdisciplinary setting combining microbial mutagenesis assays, mammalian cancer models, next-generation sequencing, bioinformatics, and machine learning. Experimental data will be integrated with
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themes: Trust, Cooperation, and Learn. Digital Futures Research Matrix What the call offers The opportunity to conduct research in a new research group at a leading university of institute within
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,” available at https://www.bth.se/english/about-bth/work-at-bth/vacancies . The position requires authorization to work with classified data. Security screening may be conducted on the selected candidate
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difference! For further information, please visit: https://www.lunduniversity.lu.se/about-lund-university/work-lund-university www.sweden.se https://www.maxiv.lu.se/about-us/careers/compensation-benefits/
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data using multivariate statistics and machine-learning–assisted approaches, in close interaction with data science collaborators Active collaboration across disciplines spanning spectroscopy, soft
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aspects of both. The first direction concerns the data-driven discovery of dynamical rules underlying developmental trajectories. The aim is to develop and analyze quantitative frameworks that learn