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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
-dimensionality and complexity of metabolomics data, requiring advanced AI/ML techniques for robust analysis and interpretation. Integration of multi-omics data (genomics, transcriptomics, proteomics, and
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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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Postdoctoral researcher in acid gas neutralization using carbonates from phosphate mine interlayers (12 mois) As part of its commitment to the circular economy and industrial waste valorization, and
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communities in soil environments. Develop and optimize laboratory protocols for characterization, and functional analysis of soil biology. Utilize high-throughput sequencing technologies to analyze soil
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. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics for real-time battery health monitoring and fault detection. Collaborate with
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applications. Collaborate with project partners and compile, analyze, and document research findings. Disseminate results through the writing of scientific publications and technical deliverables. Work closely
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(e.g., Bioconductor, Galaxy, KEGG, Reactome, STRING). Proficiency in Python, R, and Unix/Linux-based environments for high-performance data analysis. Knowledge of biological network inference, causal
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in Computational Biology. The candidates should be highly motivated and have a Ph.D. in computational biology or any related field, and a good knowledge of molecular biology. The candidate will be part
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cover 1/3 of the continental surfaces and play a crucial environmental role both at local and global scales. Forests sequester 25% of the carbon injected each year to the atmosphere by human activities
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plants. Main responsibilities: The selected candidate will be expected to: Conduct research as part of the project team. Identification of the isolated strains using 16s RNA and ITS Conduct the whole