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(or not) of their owned products? Are you enthusiastic about developing and empirically testing innovative (marketing) ways to motivate consumers towards repair? If so, then we have the perfect opportunity
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incompletely understood, partly due to the lack of physiologically relevant experimental models. This project aims to develop an advanced multicellular organ-on-chip platform that recapitulates the structural
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challenging, and skills quickly become outdated due to fast-developing technologies (AI, XR, robots). Currently, most Smart Industry companies lack human capital and knowledge to achieve their maximum potential
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, limiting user understanding, contestability, and trust. In this PhD position, you will contribute to the development of a transparent AI system to support behavioural change in nutrition. You will integrate
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telecommunications networks and urban infrastructures Change: Developing data analysis and modelling methods to understand the interdependency Impact: Better design to enhance telecom and urban performance Job
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optimally for future challenges. This PhD position is part of the SecReSy4You MSCA Doctoral Network, which focuses on developing next-generation methods for security and resilience of cyber-physical systems
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? Do you like studying physical systems with wide impact in society? Then, this PhD position is ideal for you! Information This PhD project aims to develop advanced fluid models for low-temperature
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participation of citizens. You will focus on developing adaptive learning systems that enhance the transparency and contestability of AI decisions through personalized, multimodal explanations. Your job AI is
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the development of structural color. In addition, the project will investigate the incorporation of metallic nanoparticles to produce multifunctional hybrid photonic materials with enhanced optical and
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spectrometry – to detect natural toxins in crops and water at the point-of-need. In this challenging project, you will work as a PhD student to develop novel approaches to impart chemical selectivity on easy-to