PhD Researcher in AI-Driven Multimodal Data Fusion for Rare Diseases

This PhD position at the University of Leuven, hosted by Life Science Network gGmbH, focuses on advancing AI-driven multimodal data fusion techniques to improve understanding and management of rare diseases. The successful candidate will work on innovative computational methods combining genomic, clinical, and imaging data to enhance diagnostic accuracy and therapeutic strategies. The project bridges computer science, biomedical research, and medical sciences, offering a multidisciplinary environment. Applicants should be passionate about leveraging AI to address critical challenges in rare disease research and willing to contribute to translational medicine advancements.

• Develop and implement AI models for integrating multimodal biomedical data (genomic, clinical, imaging) to improve rare disease diagnostics.
• Design and evaluate novel data fusion techniques to enhance accuracy and interpretability of AI-driven predictions.
• Collaborate with biomedical researchers to translate computational findings into clinically actionable insights.
• Publish research findings in high-impact journals and present results at international conferences.
• Contribute to the development of open-source tools or pipelines for rare disease data analysis.
• Participate in interdisciplinary workshops and training sessions to bridge gaps between computer science and biomedical research.