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specifications for generative AI. Experimenting with tuning and adapting large language models for spec-driven development. Validating your ideas through empirical studies, prototypes, and real-world data. Why is
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for these architectures remains a key challenge. This project will explore how reconfigurable/spatial computing devices can be integrated into large-scale heterogeneous infrastructures, which include CPUs, GPUs, DPUs, and
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primarily empirical, with a focus on applying modern micro-econometric methods to large scale datasets such as administrative data. The exact topic will be chosen in coordination between the successful
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aims to develop data-efficient and reliable training strategies for vision foundation models, reducing the need for large datasets and improving robustness. The project will explore strategies related
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data (i.e., large-scale assessments from the LKK project ) (Study 1 & 2); qualitative analysis of child data collected with the mosaic method (Study 3); a mixed-method analysis of the caregiver-child
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18 Dec 2025 Job Information Organisation/Company University of Twente (UT) Research Field Computer science » Cybernetics Computer science » Programming Researcher Profile First Stage Researcher (R1
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able to work with very large data and have the creativity and curiosity to work with network measures and statistics. You may also be an expert on grounded computational social science: combining large
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large language models for spec-driven development. Validating your ideas through empirical studies, prototypes, and real-world data. Why is this challenging and meaningful? You will work at the frontier
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of the North Sea maritime infrastructure through AI-enabled, human-centered, and data-driven cyber-physical threat intelligence. This large interdisciplinary project builds on insights from network
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12 Dec 2025 Job Information Organisation/Company Utrecht University Research Field Computer science » Modelling tools Computer science » Programming Geography » Cartography Geography » Human