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research experience in e-health, digital health or a related field experience of, or a documented interest in, machine learning, AI methods or large language models (LLMs) in clinical or health-related
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qualifications: Coursework or thesis work in complex systems, network science, agent-based modelling, transport modelling, urban analytics, resilience, computational social science, data science, machine learning
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multi-omics integration with advanced machine learning, including artificial neural networks, to predict disease-relevant splice variants across cardiometabolic diseases. By leveraging extensive meta
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sensing, energy-efficient computing systems, artificial intelligence (AI), and machine learning (ML), which has resulted in many collaborations with industry and other research institutes. Most of our