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https://www.universiteitleiden.nl/en/science . The Leiden Institute of Advanced Computer Science (LIACS) is the Artificial Intelligence and Computer Science Institute of the Faculty of Science of Leiden
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understanding needed to guide crop improvement, support breeding strategies, and design resilient ideotypes for future Dutch protein landscapes. Where to apply Website https://www.academictransfer.com/en/jobs
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, please contact Cécile de Morrée. Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate . Where to apply Website https
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organic matter deposited in coastal marine systems. In this project we will take advantage of recent analytical advances in high-resolution mass spectrometry which enables untargeted lipidomic analysis
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matters of scientific urgency. Where to apply Website https://www.academictransfer.com/en/jobs/357678/phd-position-in-project-mechani… Requirements Specific Requirements We look for an enthusiastic
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the design and analysis of such models. PhD position 1 will focus on developing new graph-theoretic frameworks for analyzing graph learning models, such as Graph Neural Networks or Graph Transformers. PhD
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psychometric methods to reliably and validly compare children’s, adults' and AI-models’ fluid intelligence across a series of cognitive tasks; and conducting cross-sectional and longitudinal data analysis (e.g
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extravasation into tissue, and by jointly optimizing nanobubble formulation and image acquisition, analysis and interpretation methods. As it is the most common and second-most lethal cancer in the western world
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the MRA (in particular, reuse, repair and sharing), based on a meta-analysis of existing projects, policy information and evaluations, and academic research, 2) evaluating drivers and barriers for different
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analysis of the social implications of language choices. The final dissertation will offer new insights into the interplay between language strategies and power structures in and around the selected early