30 structural-engineering "https:" "https:" "https:" "Multiple" PhD scholarships at Utrecht University
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Application deadline: 31 January 2026 Join the ERC-funded GeoTrAnsQData project and explore hybrid AI approaches to better understand, structure and formalise geo-analytical questions. This helps shape
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, this PhD project will focus on developing and applying lymph node-on-a-chip (LN-on-a-chip) platforms. Your tasks: You set up co-culture of multiple immune cell types in a physiologically relevant
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required for broader participation. You will be part of a cohort of 11 PhD candidates from multiple Dutch universities and disciplines, from social psychology and urban planning to governance studies and
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candidate to conduct interdisciplinary research that links question answering, knowledge modelling, geo-spatial analysis, and workflow construction. This PhD position focuses on developing a semantic model of
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do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. To apply, please send the following documents via the ‘apply now’ button: a motivation letter (max 2
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, you will analyze and model reading-related data to uncover relevant patterns and structures. Your tasks will include: Reviewing existing research literature across relevant disciplines and identifying
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with large spatial and temporal datasets. You must have: An MSc in Earth sciences, hydrology, civil engineering, environmental science, or a related field. A collaborative mindset and an interest in
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. Therefore, dedicated mass spectrometers and LC methods have been and are developed allowing the analysis of the structure and function of protein machineries. More information For more information, please
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security screening can be part of the selection procedures of academic staff. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. You can only apply via
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Technology group led by Gabriele Keller external link . As our research group contains core members of the popular Accelerate and Stan DSLs for machine learning and scientific computing, newly developed