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Field
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monitoring and bioelectronic medicine. The project builds on the lab's track record in flexible sensor arrays, field-effect-transistor biosensors, and functional nanomaterial interfaces, and will contribute
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sensors themselves are reaching the point that they can meet the required performance, an essential final problem still needs to be resolved. Namely, the connection of the flow sensor chip to the outside
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. Typical liquids to be administered are noradrenaline, dopamine, dobutamine, morphine, insulin, glucose and saline solution. Whereas the flow sensors themselves are reaching the point that they can meet the
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18th September 2026 Languages English English English We are looking for a PhD Candidate in Laser-Induced Graphene (LIG) Sensors for Composite Materials Apply for this job See advertisement This is
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Vacancies PhD position on hermetic packaging of microfluidic sensor chips without glue or elastomers for ventilators and multi-infusion systems Key takeaways In medical equipment, many different gas
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, for the preparation of a doctorate, contains: The development of novel spectroscopic sensors within the framework of the FWO-SBO-funded research project MOSAIC, Multimodal Optical Sensing and AI
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-efficient drone platform components integrated with multi-modal sensors and nanogenerators’. Why is the proposed project relevant? Diverse drone platforms (ground/aerial/marine robotic vehicles
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You will develop the theory that connects quantum experiments with mechanical systems to questions in fundamental physics, establishing what such experiments can and cannot reveal about nature. Job description Imagine extending decades of exquisite quantum control from atoms, ions, photons, and...
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to staff position within a Research Infrastructure? No Offer Description Sensor development at the Faculty of Pharmacy (UCM). Multidisciplinary project in materials science and sensor design applied
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24th June 2026 Languages English English English The Department of Marine Technology has a vacancy for a PhD Candidate in multi-sensor fusion and representation learning for underwater robotics