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intrinsic stability or robustness properties. You will also investigate how physical insight, prior system knowledge, and stabilizing baseline controllers can be combined with learning to improve performance
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Engineers usually want predictability. This project embraces chaos! – Excited about control theory? Then join us to build the math of chaotic sampling for greener and more secure control systems
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understanding of how light can be used to control polymer formation and structure. A key focus of the project will be chemical recycling. You will develop photocatalytic approaches to selectively break down
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questions into robust machine learning implementations, including preprocessing, model training, validation and deployment is part of your role; collaborating enthusiastically with domain specialists and
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insights to inform the development and implementation of robust mitigation measures for the achievement of climate neutrality goals. Your duties and responsibilities include: As a PhD researcher, you will
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accessibility, and dependency on corporate-controlled resources. The project aims to develop data-efficient and reliable training strategies for vision foundation models, reducing the need for large datasets and
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grid operators and other stakeholders make robust decisions when the data they need cannot always be shared? The transition to sustainable heating is one of the biggest challenges of the energy
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resilient food systems, robust businesses, and healthy societies. A transition to nature-inclusive dairy sector in the Netherlands would be pivotal to biodiversity recovery, because of its influence in
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. You will investigate multi-agent planning, learning and control methods to enable decentralized, robust, and precise aerial manipulation with CAMLs. The goal is to allow existing UAV platforms
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historical corpora. You will test whether these patterns are universal and build a robust open-source pipeline, and join an interdisciplinary team combining semantic representation, multilingual NLP, and