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                developed by the project partners will be based on two key technologies: machine learning algorithms that generate artificial yet realistic data points (synthetic health data) and secure multi-party 
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                world's fastest and most accurate radiation detector, a cancer-sniffing sensor device for smartphones, and a headphone set entirely made of microbial materials. Get to know us further by exploring VTT's 
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                RF sensors and antennas, and we are developing unique radio head with CMOS technology for these applications. Your experience and ambitions Candidates should possess basic skills in integrated circuit 
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                such as earth with different sizes of rocks. 2) Development of advanced control algorithms integrated with force and loss models to prevent overloads and hazardous situations, ensuring operational 
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                Research Infrastructure? No Offer Description Are you interested in making smart devices even smarter and more energy-efficient? Are you enthusiastic about working with projects on state-of-the-art sensors 
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                that are of practical interest. The postdoctoral researcher will contribute to the theoretical foundations of inverse problems involving wave phenomena, develop cutting-edge computational algorithms, and apply 
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                : neuromorphic algorithms, machine learning, classifier development, AI programming Key tasks include experimental and/or computational research, collaboration within the project team, publishing results in high 
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                utilized to explore how quantum protocols can be adapted to mechanical sensors in the quantum regime for various applications. Your role The experimental work in all these projects involves design of 
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                Scientists (4) to join our Quantum Sensors team at Espoo! Our team is part of VTT’s Microelectronics and Quantum Technology research area. The international quantum teams consist of experts working 
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                experimental materials synthesis, characterisation or both, and optionally, with experience developing algorithms for accelerated discovery based on data collection from automated instruments. Practical