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research applications Experience in planning and conducting field-work Experience in planning and conducting laboratory work within soil molecular analysis and bioinformatics, including qPCR, 16S rRNA/ITS
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, computer science, bioinformatics, computational biology or biostatistics Proven expertise in machine learning applied to molecular or other high-dimensional data Experience working with IBD or other immune-mediated
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research groups: (1) Clinical AI, (2) Bioinformatics and Statistics, and (3) Data Science Methods. The PhD student will be part of the Data Science Methods group, which has a strong research focus on privacy
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) Bioinformatics and Statistics, and (3) Data Science Methods. The postdoc will be part of the Data Science Methods group, which has a strong research focus on privacy-preserving techniques. CLINDA includes 17 core
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profile in animal ecophysiology Experience in one or more molecular methods (e.g. metabolomics, proteomics, enzyme kinetics, eDNA, population genetics, bioinformatics) A strong profile in interdisciplinary
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one or more molecular methods (e.g. metabolomics, proteomics, enzyme kinetics, eDNA, population genetics, bioinformatics) A strong profile in interdisciplinary research (e.g. integrating knowledge
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. Omics data handling and basic bioinformatics. Personal qualifications The successful candidate will work across plant physiology, molecular biology and microbiology and collaborate closely with the two
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science, bioinformatics, engineering, or a related data science discipline. Applicants must have documented research experience within artificial intelligence, machine learning, computational methods, or data-driven