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model utility Unlearning as an AI safety primitive — exploring how federated unlearning can contribute to removing hazardous or harmful knowledge from collaboratively trained models, positioning the work
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methods, and structured unsupervised learning. Research Environment & Collaboration The successful candidate will work at the interface of probabilistic machine learning, computational statistics, and
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–V sources from established collaborators will provide the photonic input; the student will build and characterise the QD–vapour interface itself, and characterize it using quantum-optical methods
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be supervised by Carla Groenland. You will have the opportunity to collaborate with postdocs, PhD candidates, and other faculty members of the research group in Discrete Mathematics and Optimization
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the microstructural features controlling embrittlement and establish quantitative links between microstructure and structural performance. The outcome of this research, conducted in close collaboration with Tata Steel
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. These activities will be conducted in close collaboration with the model group and other colleagues at the department as well as international partners. Further, it is expected that you can collaborate broadly with
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? No Offer Description In this unique opportunity as a PHD candidate, you will be conducting applied research in the Research Centre of Hotelschool The Hague in close collaboration with our Lector
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, complex systems analyses, automated extraction data analysis and methods-needs matching Your PhD position is part of the Academic Research Network HTA, a collaboration between the National Health Care
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capacities for dialogue, disagreement, collaboration, and peaceful conflict engagement in diverse and often polarized environments. A central component of the PhD project will be the comparative mapping
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in close collaboration with with a postdoctoral researcher and a fellow PhD candidate, you will identify microbial taxa and microbial interactions that are most strongly associated with disease