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single cell sequencing data and high-performance computing environment is highly preferred. A good understanding of cancer biology, immunology, cell biology, and molecular biology is also preferred. Proven
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coding in R, Matlab and/or Python, and already adapt to using the UNIX command line and executing analyses using high performance computing cluster. Preferred qualifications: Prior experience in analyzing
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of statistics and mathematics are required. Training experience in artificial intelligence (such as machine learning and deep learning), experience working in a high-performance computing cluster environment, and
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to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical, biological, and methodological
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pipelines, proficiency in genomic association analyses, particularly involving large-scale datasets, and familiarity with cloud computing and/or high-performance computing (HPC) environments
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selected candidates. This is a high-impact role with the potential to shape the future of rare disease research. Join us to push the boundaries of what’s possible in computational biology and personalised