CBS – Postdoctoral Position, Artificial Intelligence Applied to Multi-Omics Data Integration job with MOHAMMED VI POLYTECHNIC UNIVERSITY
Publish Date: 2026-02-09 03:15:00
Source Domain: www.timeshighereducation.com
Position Overview:
We are seeking an outstanding Postdoctoral Researcher in Artificial Intelligence (AI) and Data Science with expertise in multi-omics data integration for health and precision medicine. The successful candidate will join a multidisciplinary team developing AI-driven approaches to integrate and analyze genomics, transcriptomics, proteomics, metabolomics, and microbiome datasets 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 fusion, enabling next-generation solutions in precision health and biomedical research.
Scientific Challenges Addressed in the Position:
- Heterogeneity and high dimensionality of multi-omics data requiring 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 for comprehensive systems biology modeling.
- Identification of causal relationships and biomarker discovery through integrative approaches.
- Time-series and longitudinal multi-omics data analysis for disease progression modeling.
- Explainability and interpretability of AI models to support clinical decision-making and regulatory compliance in healthcare settings.
- Scalability and computational efficiency in processing and integrating massive multi-omics datasets from clinical cohorts.
Key Responsibilities:
- Design and implement AI/ML pipelines for multi-omics data integration, including supervised and unsupervised 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 learning, transfer learning, and data fusion techniques to integrate heterogeneous omics datasets and clinical metadata.
- Conduct…
