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We seek a postdoctoral associate with PhD degree in Physics, Electrical Engineering, Materials Science or in related fields specialized in acoustic sensors, device fabrication, and electromechanical
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are in particular targeting development of data-driven high-performance computing techniques for unbiased discovery of generative models & theory and algorithms for network inference with special reference
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sensing and control. The candidate should have strong field experience, be comfortable working in outdoor environments, and be capable of handling sensor integration and electronic systems troubleshooting
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family of printable high-gauge factor wireless sensors by building and extending our related background intellectual property. Responsibilities : Collaborate with the development of a new family of RFID
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with experience in areas such as flexible and large area electronics, neuromorphics, energy harvesting and sensors/detectors. We invite applications from dynamic individuals with demonstrated expertise
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irrigation efficiency; soil management to maximize nutrient-use efficiency. Sensors for soil characterization – pH, water content, temperature, ion-exchange, and mass transport of gases/water, etc. Phenotyping
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We are seeking motivated researchers with expertise in large-area 2D materials growth for sensor and transistor applications. The focus is on developing wafer-scale 2D materials using CVD, PLD
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in simulation, prediction, and analysis of large-scale and complex fluid systems. Special emphasis will be directed toward incorporating high-performance computing, advanced algorithms, machine
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industry partners. Design, implement, and validate advanced reinforcement learning models. Utilize reinforcement learning and evolutionary algorithms to discover new chemical materials. Publish and present
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algorithmic advances and aim at publishing them at these top venues. More details about the position can be found here. As a KAUST postdoc or researcher, you will have access to state-of-the-art research