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both on the sequence and structural level, developing and employing machine-learning tools for predicting antibody-epitope binding. In silico antibody design is a long-standing computational and
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computational biology techniques to perform antibody design both on the sequence and structural level, developing and employing machine-learning tools for predicting antibody-epitope binding. In silico antibody
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(Transcend). More about the position / Project description The candidate will develop and employ a variety of computational biology techniques to perform antibody design both on the sequence and structural
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, and single-cell sequencing. Responsibilities Perform intravital surgery to implant optical imaging windows over draining lymph nodes for long-term, real-time tracking of T-B cell interactions. Develop
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generating transgenic mouse models. Comprehensive core facilities for advanced flow cytometry, genomics, and single-cell sequencing. Responsibilities Perform intravital surgery to implant optical imaging
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to support the candidate’s career development and will be planned in alignment with their skills and goals, where possible. Learn more about career support and career-enhancing work available at NHM
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challenges. It fosters collaborations and develops advanced computational tools through a hub for multi-omics and systems biology. Project description The PhD project aims to explore how multiple layers
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experience with building Docker containers. Experience with high-throughput sequencing data analysis (e.g., CAGE, ATAC-seq, ChIP-seq, or Hi-C). Familiarity with epigenetics, gene regulation, or chromatin
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://www.combine-marv.eu/ The main focus of the team at UiO is to use advanced proteomics techniques to characterise host cell signalling pathways activated by Marburg virus in multiple human cell types
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experience with building Docker containers. Experience with high-throughput sequencing data analysis (e.g., CAGE, ATAC-seq, ChIP-seq, or Hi-C). Familiarity with epigenetics, gene regulation, or chromatin