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integrated hardware systems. Experience in integrating camera modules and sensors (I2C, SPI, UART) is advantageous, as is knowledge of microfluidic automation, including actuators like pumps, valves, and
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). Additionally, they should showcase experience in prototyping, debugging, and testing integrated hardware systems. Experience in integrating camera modules and sensors (I2C, SPI, UART) is advantageous, as is
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data, including data from electronic health records, medical images, and sensor data from wearable devices Responsible for writing up results, training and supervising students and junior staff
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-modal data from electronic health records, medical images, and sensor data from wearable devices Responsible for writing up results, training and supervising students and junior staff, preparing
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platform using AI. Involve in the development, implementation of the platform, as well as integration with multi-modal data from electronic health records, medical images, and sensor data from wearable
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of 3 years of relevant research experience. Familiarity with sensors and structural design. Strong written and oral communication skills. Proficiency in programming languages such as C/C++, MATLAB
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the design, implementation, and testing of statistical and AI software for analysing large healthcare-related data, including data from electronic health records, medical images, and sensor data from wearable
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. Requirements Ph.D. in Civil Engineering. Minimum of 3 years of relevant research experience. Familiarity with sensors and structural design. Strong written and oral communication skills. Proficiency in
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highly complex workflows. We aim to develop optimization models and algorithms to improve wafer processing sequences across semiconductor manufacturing tools, with the objectives of reducing cycle times
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wafers are processed across hundreds or even thousands of manufacturing tools following highly complex workflows. We aim to develop optimization models and algorithms to improve wafer processing sequences