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involved in: Analysis of data from medium and low-cost sensors Analysis of data from cognitive performance assessments and health survey responses Conduction citizen science-based activities in the schools
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materials exhibits prompt changes in magnetic, electronic, or optical properties upon stimuli and are promising candidates for applications in memory devices addressable by light, optoelectronics, and sensors
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—such as microtubes—while also performing embedded functions like weight and color detection. The project will combine multi-material 3D printing, sensor integration, and adaptive control, aiming to push
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measurement techniques/ sensors. Experience with system modelling and simulation (e.g., TRNSYS, Python, or similar tools). System and control engineering (e.g. digital twins, model predictive control) –pre
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quality comparable to that of experienced cardiologists. This PhD project centers on developing a framework for controlling a robotic arm equipped with a cardiac ultrasound probe and complementary sensors
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DTU Tenure Track Researcher in Low-Noise Supercontinuum Lasers and Supercontinuum Laser based Opt...
for the position. DTU Electro has more than 300 employees with competencies in electrical and photonics engineering. Research is performed within nanophotonics, lasers, quantum photonics, optical sensors, LEDs
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on the following: Combining passive and active cooling strategies. To optimize sensor types, the number of sensors, and locations withing cooling system and building to facilitate efficient monitoring and fault
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to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk). CLASSIQUE will address a suite of
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materials/ Latent thermal energy storage is an advantage. Hands-on experience with experimental setups and measurement techniques/ sensors. Experience with system modelling and simulation (e.g., TRNSYS
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of greenhouse gases including CO2 and CH4. The PhD project is part of the Horizon Europe Marie Sklodowska-Curie Action (MSCA) doctoral network (DN) ELEGANCE (machinE LEarning for inteGrated multi-parAmetric