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: Data Mining 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
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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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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
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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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well as the organic matter persistence. Responsibilities and qualifications Your tasks will be to: Use bioinformatic tools to mine metagenomic datasets for enzyme-specific sequences (oxidoreductases and/or hydrolases
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. students, and postdoctoral fellows of diverse nationalities, with backgrounds in chemistry, biochemistry, and engineering. We take pride in working as an inclusive team and we have a balanced gender
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biology, or analytical workflows. Interest in single-cell analysis, cancer biology, and translational research. Basic level expertise in computational biology (e.g., bioinformatics, machine learning), with