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analytics, modelling, and AI to turn scientific research into real-world impact. You’ll join an open, supportive environment that fosters learning and professional growth. Job requirements Your profile: PhD
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Postdoc SafePathways: Cross-Cultural Insights and Co-Designed Concepts for Schoolchildren's Mobility
of factors, such as a perceived lack of safety and different norms and values. These factors are heavily dependent on the local social and cultural context, in different settings, such as the family
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into real-world impact. You’ll join an open, supportive environment that fosters learning and professional growth. Job requirements Must-haves A PhD in a relevant field such as transportation, urban studies
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PhD candidates and close to 3000 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being
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Employment 0.8 - 1.0 FTE Gross monthly salary € 4,728 - € 6,433 Required background PhD Organizational unit Faculty of Social Sciences Application deadline 16 November 2025 Apply now Join the Work
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profile: A PhD in AI, preferably at the interface of information retrieval and machine learning; Research background in generative information retrieval, with publications in the leading venues relevant
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. Collaborate with the Catalysis Engineering Group and interdisciplinary teams to advance project goals. What we ask of you PhD in Chemistry, Chemical Engineering, Materials Science, or related fields. Strong
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community). What we ask of you We are looking for enthusiastic and curious candidates who meet the following profile: A PhD in AI, preferably at the interface of information retrieval and machine learning
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success. Requirements You are holding a PhD degree in physics or comparable discipline at the start of the position. You have prior experience in quantum computing, especially in the theory of solid-state
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data from BIM models and standards (e.g. gbXML). Development of OGC-compliant APIs to deliver real-time, 3D, and cross-sectoral urban data to the UDT platform in a private and secure manner. This will