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Bayesian framework and two specific proposed lines of research: (1) constructing suitable priors via neural networks approximations, and (2) enhancing the sensitivity and efficiency of posterior diagnostics
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version control and containerization (Docker/Singularity) Statistical Modeling: Quantitative data analysis using GLMs, Bayesian methods, or mixed-effect models to interpret complex perturbation datasets
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-based, Bayesian or matrix factorization methods for multi-omics integration. Ability to independently perform data analysis and scientific interpretation based on omics data at an internationally
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, or network-based, Bayesian or matrix factorization methods for multi-omics integration Ability to independently perform data analysis and scientific interpretation based on omics data at an internationally
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can find more information about us on the Department of Information Technology website . The announced position is placed at the Vi3-Division of the Department of Information Technology, but is also
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data types (transcriptomics, proteomics, imaging). AI/ML Applications: Applying machine learning or AI to predict gene function or discover functional relationships from perturbation data. FAIR
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transcriptomic information to discover novel protein coding regions, detect variant proteins, and identify cancer neoantigens. Our facility offers a full spectrum of MS-based applications including quantitative
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the “Apply” button. It is your responsibility to ensure that the application is complete as per the vacancy notice, and that the University receives it by the final application deadline. Applications must be
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or discover functional relationships from perturbation data. Familiarity with proteomics-specific public repositories (e.g., PRIDE) and metadata standards, ensuring FAIR data management. What do we offer
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, protocol selection and bioinformatics analysis, we hope to enable world-leading research. You can find more information at ngisweden.scilifelab.se . The employment will be placed at the Department