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packages to estimate variance components and/or in R; a desire to further develop advanced computational, modelling and algorithmic research skills, and utilize these developments into practical breeding
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1 will focus on developing new graph-theoretic frameworks for analyzing graph learning models, such as Graph Neural Networks or Graph Transformers. PhD position 2 will focus on designing scalable
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for image classification and other domains against existing open source LLM (e.g., Llama 3, Phi-3), as well as develop new kinds of attacks, for example based on evolutionary algorithms. 2. Investigate
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algorithms to guarantee the reliable operation of semiconductor machines, together with a highly innovative industrial partner in the Brainport region. If all these sounds fascinating, then this PhD position
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developing technologies for 6G? To meet the requirements of future mobile networks, network architectures need to become more agile and will include terrestrial and airborne network components linked by radio
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, privacy, and resilience. Today’s Transformers models scale poorly and assume abundant cloud resources. The research program FIND aims to deliver architectural and algorithmic breakthroughs that enable
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the device and for algorithm efficiency as compared to qubits. We will explore the use of tightly focused laser beams and their interaction with crystals of trapped ions to realize new ways to prepare and
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Description Challenge: Uncovering the interdependency between telecommunications networks and urban infrastructures Change: Developing data analysis and modelling methods to understand the interdependency
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Deep Learning (CIDL), part of the Leiden Institute of Advanced Computer Science (LIACS). As a team, we develop cutting-edge techniques for advanced computational imaging systems, combining expertise from
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Deep Learning (CIDL), part of the Leiden Institute of Advanced Computer Science (LIACS). As a team, we develop cutting-edge techniques for advanced computational imaging systems, combining expertise from