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Vacancies PhD position on Dependability Driven on Device Learning Algorithms for Embedded Neuromorphic Architectures Key takeaways Edge devices that can learn autonomously while guaranteeing
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. The proposed research examines judgment accuracy in the intensive care unit (ICU), You will investigate whether algorithmic advice can improve clinicians’ judgments, whether independent judgments or peer
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in Linux/Ubuntu environments is a plus; ● Knowledge of financial modelling or algorithmic trading is beneficial. Bonus points if you have: - Experience with backtesting frameworks or real-time model
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student, you will be embedded in the research groups Computational Imaging and Deep Learning (CIDL) and Applied Quantum Algorithms (aQa), part of the Leiden Institute of Advanced Computer Science (LIACS
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of the processing system online. Our approach will be to draw on a broad selection of tools including (deep) reinforcement learning, queuing networks, online algorithms and systems engineering. In addition, a large
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. Examples 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
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-based and index-based approaches, the sequent-peak algorithm, extreme value analysis, and multivariate copulas. Based on this, you will develop an improved method to map global energy drought risk and
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, Information Science, Data Science and Artificial Intelligence. We employ over 200 people in four divisions: Artificial Intelligence & Data Science, Algorithms, Interaction, and Software. The atmosphere is collegial and
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environment of the aQa (applied quantum algorithms) group, which is a team of faculty, postdoctoral researchers, and students across the Leiden Institute of Physics (LION), the Leiden Institute for Advanced
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consumption, create energy labels for algorithm scalability, and guide implementers in choosing more efficient algorithms. Ready to make AI more sustainable? Apply now! The goal of your PhD project is to