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values across different omics layers and platforms. Cross-omics data fusion and representation learning for comprehensive systems biology modeling. Identification of causal relationships and biomarker
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in programming (Python, Julia) (provide evidence with specific examples). Experience with statistical modelling and experimental design. Ability to work in a multidisciplinary team. Strong written and
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under different climatic and social contexts to provide decision-making tools for sustainable urban planning. Main Tasks and Responsibilities: Develop a predictive model integrating the direct and
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advanced AI/ML methods for robust analysis and integration. Data sparsity, batch effects, and missing values across different omics layers and platforms. Cross-omics data fusion and representation learning
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radar-derived surface soil moisture product using sequential data assimilation for root zone soil moisture mapping at high spatial resolution. Key Responsibilities: Assessment of different land surface