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                Employer- Delft University of Technology (TU Delft)
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                & Respiratory Care. Information Sleep is vital for health, cognitive function and emotional well-being. Obstructive Sleep Apnea (OSA) is a common sleep disorder that disrupts breathing during sleep due 
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                interaction, psychology and sociology. Core research topics are communication & technology, verbal and non-verbal communication, health communication, climate communication, information visualization, language 
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                30 Sep 2025 Job Information Organisation/Company Maastricht University (UM) Research Field Biological sciences » Nutritional sciences Computer science » Informatics Researcher Profile Recognised 
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                vibrant environment. We believe trust and excitement are crucial elements to achieving our goals, and we approach our research as teams and with the utmost rigor to make a significant impact on health and 
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                delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven 
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                , climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity as 
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                the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we 
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                international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health 
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                23 Sep 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Computer science » Informatics Computer science » Programming Engineering » Computer 
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                that can accurately predict component health and optimize repair decisions. You will develop novel data-centric approaches to Remaining Useful Life (RUL) prediction that goes beyond traditional model-focused