32 wireless-sensor-networks-postdoc PhD positions at Eindhoven University of Technology (TU/e) in Netherlands
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communication networks? Optical wireless links using highly directional steerable laser beams can securely serve a high density of devices at high data rates. Your project optimizes energy efficiency and develops
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to develop a new biosensing technology, for the continuous real-time monitoring of proteins and nucleic acids? Join us in tackling this challenge! Information Continuous glucose sensors are used by patients
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characterization to device integration. You will fabricate and test cutting-edge device architectures, including 2D Complementary FETs (CFETs), memory devices, and sensors, pushing the boundaries of what's possible
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, to mitigate user burden, monitoring should occur as minimally obtrusive and as engaging for a large audience as possible. Unobtrusive sensor technologies could complement self-reported data and may reduce the
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a PhD position in the field of metasurfaces for single-molecule biosensing. This project aims to develop a new generation of single-molecule sensors that exploit collective and localized resonances in
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Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing power, latency, and memory bandwidth issues with reliable
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. The second sub-project, a postdoc track, focusses on pedagogies or structures for guiding students in selecting competencies to be achieved as learning outcomes, through learning activities and assessment
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including faculty members, postdocs and PhDs working on diverse topics in the field of dynamical systems and control and its applications. This PhD position is jointly supervised by Nathan van de Wouw, Tom
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faculty members, postdocs and PhDs working on diverse topics in the field of control systems and its applications. This PhD position is jointly supervised by Michel Reniers and Martijn Goorden. Where
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fully funded PhD position within the LowDataML doctoral network, focusing on developing innovative machine-learning approaches for drug discovery under low-data conditions. LowDataML aims to bridge