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transformer-based architectures to create a powerful tool for understanding and predicting bacterial genomic sequences. The successful candidate will play a key role in developing and optimizing these models
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technologies. The project focuses on exploring microbial communities and their molecular mechanisms for detoxifying and transforming heavy metals under environmental or engineered conditions. The successful
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postdoctoral researcher will focus on the development of innovative high-temperature processes for the transformation, upgrading, or enrichment of mineral resources, particularly those derived from complex
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real-world applications in green chemistry and industrial synthesis. Key Responsibilities: Develop and implement AI/ML models (e.g., graph neural networks, transformer-based models) for retrosynthetic
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for detoxifying and transforming heavy metals under environmental or engineered conditions. The successful candidate will contribute to ongoing projects and develop independent lines of investigation within
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neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view learning, transfer learning, and data fusion techniques to integrate heterogeneous omics datasets
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component, and chemo-biology as well as heat treatments and their applications in industries. CBS-GPE projects aim to achieve an in-depth understanding of the molecular mechanisms of these transformations
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challenges. Skill in transforming complex data into actionable insights for research and decision-making. Proven capacity to produce high-level publications and present research results at international
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-linked research projects funded by the OCP Group.The postdoctoral researcher will focus on the development of innovative high-temperature processes for the transformation, upgrading, or enrichment
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understanding of the molecular mechanisms of these transformations to suggest new, original, more effective, sustainable, and environmentally friendly alternatives. Funding information : This position is