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of such use cases and applications compiling algorithms for use on early-generation hardware. We also encourage applicants interested in other quantum technologies such as quantum sensors and simulators, and
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. Key Responsibilities Lead AI/ML algorithm development for predicting plant water and nutrient uptake under varying environmental and growth conditions. Analyze multi-source data, including aerial and
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complicates both learning and inference processes. Another challenge is that dynamic structured data are generated by a variety of sensors and infrastructures that continuously produce, disseminate, and store
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, sensor failures, or the aggregation of datasets from multiple sources. There is a rich literature on how to impute missing values, for example, considering the EM algorithm [Dempster et al., 1977], low
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. Some field work is required for instruments, sensors and equipment setup to facilitate data collection. This position provides an excellent opportunity for the candidate looking to develop skills
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of the following topics: physical layer design for ultra energy-efficient wireless spike-based sensor node communication digital baseband design for energy-efficient terabit/sec wireless communications using
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systems for measurement processes, or innovative hardware and software for quantum computers and quantum sensors: we develop tomorrow's technology in-house for a sustainable and secure society. When will
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all project deliverables are met. Undertake these responsibilities in the project: Conduct technology review of sensor technology Develop algorithms/models for engine health monitoring Develop prototype
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sensors and readout electronics, SPECT, PET, and X-ray imaging instrumentations, image and signal processing techniques, pre-clinical and clinical applications. Develop new research areas to include
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detection, to cite a few. As telecom fibers are ubiquitous in urban environments, DAS appears as a breakthrough concept to upgrade existing fiber optic networks to acoustic sensor arrays, and a key component