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Are you fascinated by how machine learning can enhance control without compromising safety or stability? As a PhD candidate, you will develop scalable methods for expressive and flexible neural
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, using qualitative research, consensus methods and quantitative validation in an international cohort. Risk and resilience: identifying factors associated with parental distress, coping and resilience
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this project, you will develop innovative image analysis methods to improve image quality and enable advanced quantitative analyses of ^89Zr-immunoPET data, including radiomics and artificial intelligence
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of media governance. We are looking for a curious, creative, and collaborative researcher with strong training in historical research methods to investigate the contestation of the public media model from
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, distrust in epistemic authorities, and declining intellectual engagement (epistemic anomie). This project uses several quantitative and qualitative methods like (panel) survey, lab experiments focus groups
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decision-making methods that enable robust decisions for heat transition planning despite these data-sharing constraints. Rather than assuming full access to data, your research will investigate how planning
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methods like (panel) survey, lab experiments focus groups, and data donation. Each PhD Candidate will write a paper-based dissertation and strive to publish the results of the individual sub-studies in
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children and their parents. Are you interested in multilingualism, diverse research methods, and team science? Apply now! About the position Children from immigrant families often translate and mediate
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validate reproducible automated workflows for quantitative photophysical measurements to obtain optical spectra and quantum-yields. Implement AI methods to search in the parameter space that affects
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of microfluidics in the aforementioned demanding fields. This project aims to find methods to eliminate these urgent packaging issues. As the demand for advanced ventilators and multi-infusion systems grows, finding