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Machine Learning Bioinformatics The successful candidate will contribute to advancing state-of-the-art in data mining and machine learning research with applications in computational biology by: Developing
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bioinformatics including NGS (Nanopore, Illumina, PacBio) Experience with automation and coding in Python or other programing languages Experience with protein software tools like AlphaFold3, Boltz2, PyMOL
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hub in the context of metabolic diseases, such as MASLD and cardiovascular diseases. For this, we apply a range of single cell genomics technologies on clinical biopsies combined with bioinformatics
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PhD fellowship at the Copenhagen Center for Glycocalyx Research at the Department of Cellular and Mo
data science, bioinformatics, protein design, biochemistry, mass spectrometry, cell biology, molecular biology, genetic engineering, medicine or related fields. The successful candidate will join a