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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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two-year master's degree (120 ECTS points) in Biotechnology/Systems Biology/Bioinformatics or a similar degree with an academic level equivalent to a two-year master's degree. We offer a supportive
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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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integrated with bioinformatics including large language models. The PhD scholarship includes an obligation for a 9 month research stay at the Chinese Academy of Sciences in Beijing, China integrated with
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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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ecology, biology, microbiology, bioinformatics, or a closely related field is an advantage. Excellent oral and written English language skills are a requirement. Previous experience in computer programming
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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