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Field
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Michael Bronstein, AITHYRA Scientific Director AI and Honorary Professor of the Technical University of Vienna in collaboration with Ismail Ilkan Ceylan, expert in graph machine learning, invites
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data reflect real‑world disease phenotypes. Advanced analytics: apply AI and machine‑learning techniques (e.g., graph neural networks, multimodal transformers) to uncover novel biomarkers and generate
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, mobility and cost. This project aims at developing a dehydration monitoring system that fuses multiple modalities of measurement in order to enhance the quality of measurement, and improves usability by
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more effective screening and therapy. The postholder will focus on developing and applying advanced computer vision and machine learning methods for multimodal imaging and real-time analysis in
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. The successful applicant will integrate multi-modal live imaging and omics data using AI-based pipelines to identify and refine early disease phenotypes, laying the groundwork for therapeutic intervention
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learning, and innovative thinking. Join us at RCSI, where your contributions will be recognised, and you will be part of a dynamic team making a real impact on global health. About PRiCAN PRiCAN (Primary
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Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative
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Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative
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reactions. We welcome applicants from diverse backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate
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of machine learning models for object detection, classification, and outlier detection across multiple sensor modalities. Depending on previous experience, provide scientific oversight to volunteers, students