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on real-life data from the maritime industry. As part of the PhD, you will be following advanced courses to extend your skills, implement and test algorithms, and learn to write scientific papers. As part
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algorithms for resource-efficient learning, for example via data selection and filtering (leveraging that not all data is equally informative). You will also investigate complementary approaches that reduce
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address domain-specific challenges in biomedical applications. The PhD project will focus on translating and enhancing cutting-edge algorithms from AI research into concrete applications in biomedical
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composites toward a new generation of smart structures with built-in sensing and intelligence. By integrating optical fibre sensors directly into composite materials and combining them with physics-based
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in a team environment Highly organized with excellent communication and interpersonal skills Preferred Qualifications: Experience with eye-tracking or wearable sensor technology Background in clinical
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the Unconventional Communications and Computing Laboratory (UC2), led by Dr Michael T. Barros, which develops modelling and algorithmic methods for networked communication and computation under real-world constraints
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solutions using first motion. Experience in full waveform inversion using innovative tools (e.g. ISOLA) and methods (ML), earthquake location algorithms, computer programming and geophysical equipment
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project’s focus is to: Conduct cutting-edge experiments to investigate how surface texture affects seal performance and explore the use of an ultrasonic sensor for real-time monitoring. Experiment with
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, nanophotonics, lasers, quantum photonics, optical sensors, LEDs, photovoltaics, ultra-high speed optical transmission systems, bio-photonics. Technology for people DTU develops technology for people. With our
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G protein and poly-mer brushes. Research experiments should make it possible to determine the limit of detection, specifici-ty and selectivity of biosensors. The sensor response will be realized