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closely related to the subject of the PhD-project, but more practically oriented. The PhD-project focuses on the development of advanced machine learning methods for statistical arbitrage trading. You will
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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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to the full development pipeline: from algorithm design and implementation to clinical integration and evaluation. You will also work on improving prognostic models using (neuro-symbolic) AI and develop
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). The CIDL group develops cutting-edge techniques for advanced computational imaging systems, combining expertise from Mathematics, Computer Science, and Physics. The aQa group studies quantum algorithms and
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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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on developing new ML approaches to challenging quantum problems, with a strong focus on making these approaches interpretable, reliable, and scalable. In this position, you will learn about state-of-the-art deep
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Aspects of Clinical Decision Support Systems. The lab is an interdisciplinary collaboration between several universities and other partners. Your job Your main task will be to develop a multi-agent logical
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will develop a method to help development teams choose the right algorithm and right hardware. This can be done by measuring (during the above-mentioned experiments) how the algorithms are constrained