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Field
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-disciplinary research environment Desirable criteria 1. Experience in devising and developing novel machine learning algorithms 2. Hands on experience with ROS and physical robots 3. Excellent
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research aims to develop new AI for shared human-AI decision-making in healthcare imaging. This post is focused on AI-assisted ultrasound guidance building on the group’s prior work on video and multi
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around 15 are PhD students. The work environment is open and welcoming, striving to provide each employee with the opportunity to develop personally and professionally. The field of solid mechanics relates
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challenges raised by the increased digitalisation of society. Our in-house iLab develops value-based prototypes and designs. Researchers at iHub are organised around themes, such as algorithmic discrimination
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data, metabolomics and/or proteomics. Develops robust pipelines for data annotation, analysis, and quality control. Creates analytical algorithms and tools to address scientific questions with big data
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will apply state-of-the-art machine learning algorithms and custom disease-relevant genomic datasets (e.g., coronary artery single-nucleus chromatin accessibility and RNA sequencing) to develop targeted