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Field
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-truth data from manual measurements and IoT sensors. The overarching objective of the PDF will be to integrate these datasets to gain new insights into tree growth and response dynamics and trends, and to
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. This role offers an exciting opportunity to work on developing and validating models for wearable sensors aimed at improving human movement, rehabilitation, and fitness engagement. An important component of
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to analyze and interpret unstructured data (e.g., maintenance logs, sensor data, technical reports) for predictive insights Collaborate with domain experts to integrate LLM-based solutions into predictive
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optimizing high-performance C++/C# software modules for real-time control, sensor fusion, and data analysis; developing unity‐based visualization and user-interaction interfaces, including 3D modelling
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a set of suitable EGG sensors, thereby enabling an electrogastrogram. This device will be created by SYMME in collaboration with the expertise of LIP/PC2S. Objective 2: Once the device has been
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probabilistic modeling of weak signals in the image related to sensor noise developed on JPEG images [Taburet et al., 2020, Giboulot et al.,2021, Giboulot et al.,2022]. The modeling of the sensor noise will be
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functions in a non-invasive way through sensing the tiny magnetic fields produced by neuronal currents. Today, this need is primarily met by quantum sensors that must be operated at cryogenic temperatures
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the advent of the Internet of Things (IoT), any sensor can be interfaced with a local network or the Internet. This massive deployment has created many security issues and associated solutions
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) to predictive maintenance challenges. Develop and fine-tune LLMs to analyze and interpret unstructured data (e.g., maintenance logs, sensor data, technical reports) for predictive insights Collaborate with domain
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mentor including (but not limited to): Design, deploy, and maintain environmental sensor stations, including quarterly travel for installation and servicing to flood prone regions in Illinois and