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chemistry, chemical biology, biochemical and thermal reactions. Research at CBS is organized around several major areas, which aim to answer challenging industrial questions, from complex chemical and
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between objects. A common way to represent a graph is to use the adjacency matrix associated with the graph. However, adjacency matrices only model networks with one kind of objects or relations between
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
, and Precision Health. The project aims to leverage AI and machine learning (ML) to analyze complex metabolomics datasets and address key health challenges, including biomarker discovery, disease
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which complex interactions involving rock, soil, water, air, and living organisms regulate the natural habitat and determine availability of life-sustaining resources”. Its limits range from the top of
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interpretation of remote sensing data, allowing for rapid decision-making in critical situations, such as during natural disasters. AI models can process big datasets efficiently, helping to make informed
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develop innovative solutions based on the analysis of urban data (big data, IoT, GIS) to monitor and improve public health. You will contribute to modeling smart cities with a focus on health and designing
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fertilizers is preferred but not mandatory. Experience in experimental data analysis and modeling of nutrient release processes. Hands-on experience in field preparation and establishment of multisite field
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; Assess the effect of using organo-mineral resources on soil carbon stock in the field; Implement agronomic assay to evaluate the stability of clay-humic complexes under culture conditions and how
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; Implement agronomic assay to evaluate the stability of clay-humic complexes under culture conditions and how an intense of microbial activity contributes into the process of stabilization of organic matter
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to uncover biomarkers, therapeutic targets, and mechanistic insights into complex diseases. The project addresses critical challenges in personalized medicine, disease stratification, and multi-modal data