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Interventions Our goal: To make digital health interventions more effective by predicting and improving adherence through Artificial Intelligence (AI) and machine learning (ML). Your colleagues
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comprehensive and trustworthy AI models for subtype prediction, significantly influencing clinical decisions and personalized treatment strategies. The current project funded by NWO is a continuation of the
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predicting and improving adherence through Artificial Intelligence (AI) and machine learning (ML). Your colleagues: An interdisciplinary team of scientists working across Maastricht University and FH Joanneum
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, electrical engineering, technical medicine, or a related field. You have a solid background in biomedical signal analysis, physiology dynamic system, and machine learning technologies, and preferably have
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Experience with using inference/machine learning tools and basic programming is a plus As a university, we strive for equal opportunities for all, recognising that diversity takes many forms. We believe
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Experience with using inference/machine learning tools and basic programming is a plus As a university, we strive for equal opportunities for all, recognising that diversity takes many forms. We believe
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-privacy-in-… Requirements Specific Requirements You have a Master’s degree in electrical engineering, computer science or a related area relevant to the position. You have a background in speech processing
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with industries in the supply chain and end manufacturers, guaranteeing relevant research in a mixed industrial and academic environment. About the organisation The faculty of Electrical Engineering
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simulations. Job Description Are you passionate about bridging computational modeling with clinical cardiology to solve real-world healthcare challenges? We're seeking a PhD candidate to develop innovative
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advantages for manipulation and locomotion, but current control algorithms do not fully exploit their capabilities. Most rely on approximations tailored for rigid systems or require extensive sensing and