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to handle the massive amounts of data generated by novel high-throughput scMetaG methods. Here, the PhD student will develop novel bioinformatic methods and tools, which can be used to analyze massive amounts
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, existing bioinformatic tools are not equipped to handle the massive amounts of data generated by novel high-throughput scMetaG methods. Here, the PhD student will develop novel bioinformatic methods and
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dimensionality reduction methods), systems biology analysis (including machine learning and other AI techniques), statistical tools focusing on analysis of complex longitudinal data, and how different types
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opportunities for all. Contact For more information, please contact either Professor Afzal Siddiqui, asiddiq@dsv.su.se , or Director of PhD studies, Åsa Smedberg, studierektorF@dsv.su.se . Application Apply
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attention to detail, as well as the ability to manage experimental work and data analysis simultaneously. Since the project involves international collaboration and fieldwork, good communication skills and an
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experience in large-scale quantitative and functional proteomics Experience in sample preparation of cells for quantitative proteomics Strong skills in quantitative proteomics data analysis using R, as
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collaborations across research groups and external partners in academia and industry. The PhD student will join a vibrant scientific community dedicated to developing sustainable, data-driven, and ethically
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industry. The PhD student will join a vibrant scientific community dedicated to developing sustainable, data-driven, and ethically responsible breeding strategies for modern animal production systems. Read
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proteomics Strong skills in quantitative proteomics data analysis using R, as well as knowledge in bioinformatics Solid understanding of mitochondrial functions and cellular metabolism Experience in cell
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about the departments is available at: Project description This PhD project will explore how Artificial Intelligence, in particular AI-based simulations, data-driven modelling, and generative systems