Scientific Co-Director, Data Science and Multimodal Integration

REQUIRED: Ph.D. in computer science, computational biology, data science, or a related field with a strong emphasis on AI/ML applications; a minimum of seven years postdoctoral or equivalent research experience applying AI, machine learning (ML), and deep learning (DL) techniques to biological data; experience must include evidence of original or collaborative scholarship documented by publications, software, or deployed intelligent systems; demonstrated expertise in statistical learning, ML, DL computer vision, and NLP methods applied to omics, imaging, and clinical datasets; programming skills with experience in ML/DL frameworks; data visualization and EDA expertise; multi-modal data integration and representation learning across diverse data types; and shared resource and leadership or supervisory experience. PREFERRED: Experience with data governance, FAIR principles, and regulatory compliance; knowledge of explainable AI (XAI) techniques and their application in biomedical contexts; experience with federated learning or other advanced AI paradigms; experience integrating AI models into pipelines; and familiarity with biomedical ontologies, knowledge graphs, or semantic data integration.

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