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of LNPs under various storage conditions, the aim is to develop formulations with both high performance and improved stability. The work includes the design and systematic screening of LNP formulations
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Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create globally leading computational and data science capabilities in Sweden
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of approaching reconstruction and variability analysis. The project combines applied mathematics, computational imaging, and structural biology. You will develop algorithms, implement and test software tools, and
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, the interactions between plants and microorganisms, and other forms of stress such as plant growth and development, biotechnology and metabolic manipulation, regulation of gene expression, population genetics, and
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. The goal of this project is to advance gene regulatory network (GRN) inference from multi-omics data by developing novel AI techniques that exploit the knowledge of gene perturbations (experimental design
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. The goal of this project is to advance gene regulatory network (GRN) inference from multi-omics data by developing novel AI techniques that exploit the knowledge of gene perturbations (experimental design
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of cell nuclei We are actively seeking a highly motivated PhD student with a passion for developing experimental methods to join our team. In this role, you will be involved in a groundbreaking project