42 multiple-sequence-alignment positions at Technical University of Denmark in Denmark
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modifications using high-resolution mass spectrometry and AI-based de novo peptide sequencing. Develop and apply machine learning models to predict protease activity and substrate specificity, integrating protein
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members. You will collaborate closely with immunology research groups and external stakeholders to align the yeast engineering with direct applications and emerging needs in immunological research
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consumers. You'll gain deep interdisciplinary experience—combining multiple data layers and approaches including bioinformatics, machine learning, food safety management, regulatory science, genomics and user
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susceptibility testing (AST). Provision of technical guidance and training on AST methods and whole genome sequencing (WGS) for organisms e.g. Escherichia coli , Campylobacter spp., and Staphylococcus aureus
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, next-generation sequencing such as long-read sequencing, and high-throughput analysis techniques. Primary tasks: Culture human T cells and cancer cells Design multiplexed CRISPR strategies Analyse
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the development of γδ T cells and their importance in various diseases, such as cancer and inflammation. Technically, our work is heavily focused on flow cytometry and single-cell RNA-sequencing and as a successful
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ontologies and knowledge graphs that represent the data structures and processes across our facilities. A key part of your role will be to ensure alignment with best practices and existing community standards
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/scripting (e.g., Python, R, or Bash) Familiarity with next-generation sequencing data and genome assembly tools Strong analytical and problem-solving skills Excellent written and spoken English communication
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international partners to align experimental designs, protocols, and data standards across collaborating institutions and scales. This collaboration will support the generation of coherent, high-quality datasets