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) or reactive transport simulation codes (e.g., OpenFOAM, StarCCM+, PFlotran, TOUGHREACT, PHT3D etc.). Good programming skills in C/C++, Fortran, or Python. Knowledge and experience with HPCs. The work will be
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both of these is a strong advantage. Experience with the application of ML/DL approaches to omics data, computational tool development, multi-omics data integration, and knowledge of cancer biology and
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release of Pol II from promoter-proximal pausing and facilitate productive Pol II elongation along gene bodies. We aim to exploit the knowledge on basic principles of gene regulation to help devise novel
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Knowledge of multi-modal data integration, gene regulation, cancer, and/or network biology is considered an advantage Strong analytical and problem-solving skills with the ability to develop and maintaining
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GBIF), conservation knowledge (e.g., the World Database on Protected Areas), environmental (e.g., remote sensing), threat (e.g., land use change), digital (e.g., Wikipedia), and socio-economic (e.g
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, the Digital Precision Cancer Medicine Flagship (iCAN), and among others. Your mission To qualify, applicants must hold a PhD in computational biology and possess extensive knowledge of biomedical sciences. A
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computational biology and possess extensive knowledge of biomedical sciences. A strong publication record and a solid background in computational RNA biology, particularly in alternative splicing regulation