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to microclimatic variations induced by local vegetation. The researcher will contribute to the analysis of vegetation–climate–technology interactions to optimize energy yield in environments subject to climatic
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learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
metabolomics data from clinical studies. Apply deep learning models (e.g., autoencoders, variational autoencoders, graph neural networks) for biomarker discovery, disease classification, and patient
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of the continent precipitation), surface roughness and aerosols emission. At longer timescales, forests, via the formation of soil organic matter, erosion and deposition in the ocean, play an essential role in
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of the continent precipitation), surface roughness and aerosols emission. At longer timescales, forests, via the formation of soil organic matter, erosion and deposition in the ocean, play an essential role in
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the VEGF pathway. However, challenges like adverse events, drug resistance, tumor recurrence, and lack of biomarkers limit their effectiveness. Further research into angiogenesis mechanisms, drug development
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on analyzing satellite-derived data (Sentinel-3, Landsat) to monitor coastal ecosystem changes. Develop workflows in R, Python, or MATLAB to process and analyze ocean color data, with a focus on chlorophyll-a