15 operations-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions at Eindhoven University of Technology (TU/e) in Netherlands
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processing to unlock fiber capacity and relevant higher layer protocols required to operate modern optical communication networks. Based in the purposely built FLUX building at the TU/e Campus, the ECO group
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://www.academictransfer.com/363735/ Work Location(s) Number of offers available1Company/InstituteTU/eCountryNetherlandsCityEindhovenPostal Code5612AZStreetDe Zaale Contact City Eindhoven Website http://www.tue.nl/ Street De
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performance and reliability of active components such as lasers and amplifiers Investigate the science behind yield and manufacturability by developing predictive models to connect the physics and chemistry of
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Integrated optics is currently experiencing unprecedented growth, driven largely by the rapid expansion of artificial intelligence (AI), cloud computing, and high-performance data processing
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Are you fascinated by application-oriented research in mathematics and eager to work at the interface of numerical optimization, optical design, and uncertainty quantification? In this PhD project
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the trade-off between access to view and the amount and quality of daylight and nature content provided by a nature-inspired façade? These are some of the scientific challenges you will work on in this PhD
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design with real-world materials performance and explore how sustainable polymers can be integrated into advanced applications. By bringing together photochemistry, polymer chemistry, recycling, and
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stations is proving inadequate. To address this gap, robust indoor infrastructure is essential for seamless wireless access to end users. With fiber access being pushed closer to the end devices (Fiber
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design possible in which even the small details can be readily incorporated into the electromagnetic model for robust performance analysis? Information Antenna and RF systems play a pivotal role in society
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process. This project offers a unique opportunity to work at the intersection of machine learning and control theory. You will develop rigorous theory and scalable computational methods for certifying