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Field
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efficient, adaptive use of multistable networks, offering an alternative to energy-intensive digital systems with rigid bits and separated memory and computation. In this project, we aim to design and realize
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fascinated by the incredible capabilities of neural networks? Are you interested in applying theoretical methods to understand computational efficiency in neural systems? If so, come and join us as a PhD
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using appropriate arguments and communication styles. Networking skills: You establish connections easily, maintain relationships, and actively use your network to initiate and strengthen collaborations
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addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying
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technology for the forthcoming generation of highly energy-efficient computing systems. FeFETs are programmable, non-volatile silicon devices that enable innovative architectures to efficiently execute complex
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seeking a highly motivated PhD student to join our team to work on the design and implementation of Oscillatory Neural Networks (ONNs) for physics-based computing applications. You as the candidate will be
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seeking a highly motivated PhD student to join our team to work on the design and implementation of Oscillatory Neural Networks (ONNs) for physics-based computing applications. You as the successful
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opportunities to expand your network and to collaborate with colleagues from different institutes and organizations. Terms of employment Depending on education and experience the minimum salary is €3.546 and the
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19 Sep 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Programming Engineering » Computer engineering Engineering » Electrical
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net salary. Nice, right?