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for intelligent brain-computer interfaces? We are offering a PhD position in analog/mixed-signal CMOS circuit design for EEG and wearable sensor interfaces, as part of a pioneering project focused on assistive
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development of implements for managing main and support crops in the field, tested on stationary gantry robots and mobile platforms. Work includes lightweight, structurally optimized mechanical design, sensor
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, at DTU Electro, the Technical University of Denmark, we are seeking a candidate for a PhD position to research key SiC on insulator (SiCOI) devices i.e. arrayed waveguide gratings (AWGs) and optical
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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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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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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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PhD Scholarships in Piezophotoacoustic Technology for Minimally Invasive Endoscopy - DTU Health Tech
sensing the backscattered ultrasound signals. You will join a laboratory with expertise in photonics, piezoelectric materials and device fabrication methods for sensors and actuators, working under
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agricultural robotics and new sustainable farming practices. The PhD projects will be combining new sensor systems and perception algorithms. So, if you are one of the 2 selected applicants, your primary
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with researchers at DTU and KTH, you will help develop an integrated decision-support system that: Uses real-time sensor data and AI models to assess risk scenarios. Dynamically recommends optimal