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microbiome supplement essential micronutrients to the human body? To answer these questions, the postholder will be primarily working with metagenomic data from diet interventions, using machine learning
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methodologies in machine learning and causal inference applied to human health. Read more about NCRR here . Your job responsibility With a motivated, interdisciplinary team of approximately 70 researchers and
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) to analyse the data by advanced statistical/chemometrics and machine learning tools, iv) to couple metabolome data with other omics datasets (e.g., genomics, lipidomics, metallomics, and others). Main target
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, and Bash Excellent communication skills You might also have Familiarity with modern machine learning, in particular large language models Experience with the design and implementation of web interfaces
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advanced statistical/chemometrics and machine learning tools, iv) to couple metabolome data with other omics datasets (e.g., genomics, lipidomics, metallomics, and others). Main target areas are drug
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Description This PhD project bridges computational neuroscience and machine learning to study the mechanisms of active forgetting—or unlearning—through the lens of both biological and artificial systems
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implementing innovative technologies and strategies driven by significant advances in computational biology, including bioinformatics, systems biology, and machine learning applications. The Head is expected
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of artificial intelligence (AI) and biomedical engineering. Research directions include deep learning, natural language processing, brain–computer interfaces, and their applications in disease prediction, drug
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. Meanwhile, our Master’s and PhD programs continue to expand, introducing new specializations in Statistics and Data Science, Computational Biology, and Human-Computer Interaction. Why Join MBZUAI? Top-Tier
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how are these impacted by different land use scenarios? How can we use machine learning to predict soil microbiomes from either pristine or agriculturally used soils, predict their functional capacity