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spirit and is interdisciplinary, covering bioinformatics, statistics, machine learning/AI, and computer science. Project description The postdoc will apply machine learning/deep learning approaches along
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will join an international team good command of written and spoken English is necessary. As a formal qualification, you must hold a PhD degree (or equivalent) in Allergology, Immunology, Bioinformatics
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development and application of single-cell proteomics by MS (scp-MS) workflows Advanced computational/bioinformatics analysis skills Experience with mammalian cell culture techniques, ideally including
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of the IML group within prediction of T cell immunogenicity and immunoinformatics in general. You will work with nearby bioinformatics, postdocs and PhD students working on other projects within the group and
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the competences of the IML group within prediction of T cell immunogenicity and immunoinformatics in general. You will work with nearby bioinformatics, postdocs and PhD students working on other projects within
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regulatory networks that are active in blood cells in health and disease. The successful candidates will have a PhD in Bioinformatics, Computational Biology, Biostatistics or in a related quantitative field
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collaborating on a number of spatial transcriptomics projects unrelated to cancer and you will be taking part in building a strong local community focusing on the bioinformatics aspects of these types of data
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Engage in teaching and supervision as required Expectations of qualifications PhD in Bioinformatics, Computer Science, Physics, Engineering, Bio-engineering, or equivalent Excellent track record in
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biology, genetics and basic human biology, including chemistry, biochemistry, physiology, as well as anatomy. Key criteria for the assessment of applicants Applicants should hold a PhD degree in cell
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collaborating on a number of spatial transcriptomics projects unrelated to cancer and you will be taking part in building a strong local community focusing on the bioinformatics aspects of these types of data