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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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: Conduct original design-based research within the field of education, resulting in a PhD thesis. Collaborate with other PhD candidates, postdocs, and societal partners across the consortium, including
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) assessment. You have affinity with, or experience in, advanced statistical analyses (including linear mixed-effects models and computational learning models) in R or similar statistical analysis tools. You are
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teams to explore the long-term effects of repetitive traumatic brain injury (rTBI) in both humans and mouse models. Join us! This PhD position offers you the opportunity to work at the crossroads
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Na+ transport, interfacial phenomena, and performance degradation induced by e.g. salt accumulation or Al deposition. By leveraging your experimental data with the modelling approach
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training data, when these are available, and also to learn from real-time, potentially non-IID, streaming data; should be able to track the evolution of key features and achieve model plasticity while
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tailor your employment conditions through our Terms of Employment Options Model. In this way, we encourage you to keep investing in your personal and professional development. For more information, please
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kinetics under physiologically relevant conditions Conduct in vitro biological validation using primary human cells such as osteoblasts and mesenchymal stromal cells Develop advanced 3D culture models
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tailor your employment conditions through our Terms of Employment Options Model. In this way, we encourage you to keep investing in your personal and professional development. For more information, please
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bonus contribution to commuting expenses optional model for designing a personalized benefits package a wide range of sports facilities which staff may use at a modest charge Additional comments Do you