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of psychology, digital health, and artificial intelligence to advance the development and validation of voice-based tools for mental health monitoring in diabetes. The project will leverage data from the Colive
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, including the development and use of 3D models and the study of extracellular vesicles Analyze high-throughput data sets using R or similar software Present research findings in meetings Document performed
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. In addition, the participants will take part in a 7-day "ecological momentary assessment" at each of these three measurement points, which will collect detailed information on the dynamics of stress
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. To do this, knowledge or willingness to be trained in advanced statistical modelling, ideally with an interest in methods for causal inference in observational data, is strongly preferred. Using various
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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to develop a research line related to the assessment of these processes in daily life (e.g., daily diary studies, ecological momentary assessment) and the combination of self-report and sensor-measured data
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of the group For more information, please contact professor J.S. Coron (jean-) or check the website www.crypto-uni.lu . Your profile Master's degree in computer science or mathematics Good programming skills
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constructively towards collectively defined research goals together with colleagues and collaborators Contribute to the teaching activities at the University of Luxembourg For further information, please contact
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and stable?- How do models perform on heterogeneous data (e.g., federated or personalized learning)?- Can smaller, energy-efficient models achieve strong performance on specialized tasks?Position
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and respect for our employees and students. General information: Contract Type: Fixed Term Contract 36 Month Work Hours: Full Time 40.0 Hours per Week Location: Campus Belval Planned Start Date: October