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understanding on the origin of nucleic acids that are shed in liquid biopsies, such as blood, using cancer models (mouse and rat) and patient samples of neuroblastoma disease, a rare childhood cancer. Nucleic
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drive neuroinflammation in synucleinopathies and other neurodegenerative diseases. The candidate will employ advanced in vivo models and spatial technologies to dissect the roles of tissue-resident
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foundation models and integrative theories of biological systems, and towards innovative AI-driven biotech applications in synthetic biology, agro-tech, and personalized medicine. AI-driven research at VIB.AI
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of microbiology and laboratory automation. We are looking for a highly motivated PhD candidate with a strong engineering mindset and a keen interest in AI, automation and microbiology. Prior experience in
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on cancer metastasis and novel metabolic pathways. We exploit mouse models, genetic engineering, metabolomics and single cell & spatial multi-omics analysis to gain groundbreaking insights into metabolism as
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validate the identified key (epi)genetic molecular and explore their therapeutic potential in vitro and in vivo disease models. Profile The candidate should: have an MSc in Systems Biology, Molecular Biology
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systems and computational biology. Models include yeast, fly, mouse, and pluripotent human cell systems. Research groups have access to state-of-the-art research and top-notch support core facilities and
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sequencing and transcriptomics, and iPSC-based disease modeling to better understand the genetic etiologies of intractable epilepsy. The team is part of the European STXBP1 consortium . About the project