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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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decision-making, you will have the opportunity to develop your own insights, collect data, and share your findings with both scientific colleagues and partners from professional practice worldwide. Under
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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
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currently lack guidance on how to create sustainable systems. You will develop a method to help development teams choose the right algorithm and right hardware. This can be done by measuring (during the above
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verification, and proof assistants. Your focus will be on developing frameworks that pinpoint and explain the root causes of failures in interacting programs - a key step towards ensuring fault-tolerance. While
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operations. The goal of this project is to conceive, develop, and evaluate optimization models and algorithms for increasing the economic efficiency of last-mile delivery operations, including routing
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contextual factors foster or hinder the development of the critical digital literacy skills necessary to do so? The rise of algorithmic personalization, AI-powered information sources and generative AI is
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and the learning performance, or using causal representation learning for developing more effective and interpretable MARL with communication algorithms. As a PhD candidate, you will primarily perform
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will be part of an interdisciplinary team within the Department of Artificial Intelligence at Radboud University. Your research will involve a combination of theoretical work, algorithm development, and
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justifications impact trust and effectiveness within human-AI teams? As a PhD candidate you will conduct research around the notion of justifiability, developing agent architectures for justified agency, and