9 algorithm-"Multiple"-"U"-"Prof" PhD scholarships at Leiden University in Netherlands
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optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware
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., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware optimizations (e.g., automated pipelining). The PhD student will be supervised by Nusa Zidaric. Key
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limitations. The field of interpretable machine learning aims to fill this gap by developing interpretable models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data
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interpretable models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data mining has allowed us to obtain insights from large amounts of data for decades, and it is worth
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optimisation algorithms to optimize the designs. We now hire three PhD candidates who be based at LIACS (Leiden University) and spend several months with industry and academic partners abroad. The GenAIDE
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across scales, combining multiple fields including physics, mathematics, astronomy, history & philosophy of science, and social science. Its approach to societal engagement throughout the project’s 5-year
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of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world network data
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steelmaking technologies (e.g., Direct Reduced Iron with hydrogen) and exploring long-term transition pathways through prospective LCA. It will evaluate multiple environmental impact categories, identify
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innovative steelmaking technologies (e.g., Direct Reduced Iron with hydrogen) and exploring long-term transition pathways through prospective LCA. It will evaluate multiple environmental impact categories