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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Job description Quantitative analysis of lipid nanoparticles (LNPs) using Cryo EM is challenging due to heterogenous
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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research environments in Computational Science, the research and education has a unique breadth, with large activities in areas such as numerical analysis, mathematical modelling, development and analysis
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visualization and scientific communication Extensive knowledge of relevant machine learning and AI techniques Exceptional collaborative abilities Self-motivated individual with ability to work independently
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existing genomic datasets and enable analysis of gene regulation at cell-type resolution. The project places particular emphasis on ensuring high data quality and developing robust methods that can be