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brings together expertise on transition management and Science and Technology Studies (STS). The main goal is to further co-develop with the field hands-on methods to support the responsible, societally
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expected to be able to act independently as well as to collaborate effectively with members of a larger team and supervise Master students. Good English skills are required. The work takes place in Delft
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approach that combines semantic material data, design-for-circularity, and hub logistics to scale high-quality reuse in regional infrastructure ecosystems (primary focus: Twente; validation: Brabant). Reuse
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to the adaptation of the Environmental Noise Directive for these new technologies. Your main focus will be to develop machine learning-based drone noise models that will be able to generate an accoustic footprint
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career and not yet have been awarded a doctoral degree at the time of recruitment. At the time of the application deadline, you must also have a Master's degree and must not have resided or carried out
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who wants to grow as a scientist. You are team-oriented, open to providing and receiving feedback, and keen to engage in scientific discussions. You either hold a Master's degree in Neuroscience
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to the occurrence of rebound effects. The process is envisioned to comprise four main iterations. Involving experimentation with different forms of designing and aesthetics, developing and deploying working
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, schools, communities, and online spaces – we hope to uncover the social, emotional, and behavioral consequences that cannot fully emerge in experimental paradigms. Planned methodology includes primary data
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networks, with a primary focus on network size, composition, resources, and overlap. In addition, you will work closely with the SHINE postdoctoral researcher to collect qualitative data aimed
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that the language of instruction of their entire university education (bachelor and master programme) was English, or; – scoring at least 100 on the TOEFL iBT test or 7.5 on the IELTS test. Two (academic) reference