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Open nowPosted 19 hours ago

Scientist

EURES job mobility portal314,718 open roles

Where
Utrecht, Netherlands
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Your applicationOpen nowScientistEURES job mobility portal · Utrecht, Netherlands

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  4. 14.3%14 days
  5. 33.7%30 days
This job: posted 19 hours ago

The posting

NL NEDERLAND & BELGIË STEL VACATUREMELDING IN WAAR WIL JE WERKEN? Research & Innovation Scientist - Bioinformatics - Netherlands - Utrecht - Hybrid - Permanent Full-Time - Posted: 30 Sep 2026 Scientist - Bioinformatics About the job Join the Gut Microbiome Team at Danone's Global Research & Innovation Centre in Utrecht and contribute to advancing our understanding of the relationship between nutrition, the gut microbiome and health. As a Scientist Bioinformatics, you will play a key role in generating biological insights from microbiome, clinical, nutritional and multi-omics data, helping translate cutting-edge science into evidence that supports innovation and health-focused research. Working at the intersection of biology, nutrition and data science, you will combine computational approaches with biological understanding to extract meaningful insights from complex datasets. Your work will help answer important scientific questions, support research and clinical programmes, and contribute to the development of new nutritional solutions grounded in robust scientific evidence. As part of a highly collaborative and multidisciplinary environment, you will work closely with microbiologists, clinicians, nutrition scientists, data scientists and other research partners. Together, you will contribute to advancing microbiome science while supporting scientific publications, intellectual property generation and innovation initiatives across Danone's research ecosystem. Key Responsibilities - Analyse gut microbiome data, particularly shotgun metagenomics. - Investigate relationships between the microbiome, nutrition and health. - Analyse microbial genomes and sequencing data. - Integrate microbiome data with clinical, dietary, metabolomics and other biological data. - Apply appropriate statistical methods to complex biological datasets. - Develop reproducible workflows using R/Python, Linux, Git and workflow-management tools ...

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