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the development of fusion energy, a potentially limitless energy source. PPPL is also using its expertise to advance research in the areas of microelectronics, quantum sensors and devices, and sustainability
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Implementing Bayesian networks and uncertainty quantification techniques to account for sensor noise and model confidence limits Designing, training, and fine-tuning computer vision models to extract clinically
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thinking, and analytical reasoning. High level of English. Advantageous: Experience with Python and/or MATLAB. Experience with health data, metabolomics, chemical instrumentation data, or sensor signals
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; develop and validate an astrodynamics-based orbit determination algorithm using TFC, including hybrid solutions with stochastic filters (eg, EKF or UKF); integrate and calibrate optical sensors and develop
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the HolistIC project , which develops ultra-low-power system-on-chip designs for next-generation intelligent audio IoT sensors. Your Role and Goals As a Doctoral Researcher, you will: Design energy-efficient
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rate, and wearable sensor data. Develop and validate comfort prediction models targeting high prediction accuracy using a dynamic driving simulator and real-world operating conditions. Integrate thermal
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environment. Our research facilities include access to state of the art pilot plants, ability to use a range of sensors and expertise in process modelling and design. The PhD project will be undertaken in
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project, which aims to create a technological ecosystem to support agricultural decision-making. It combines multiscale data collection from calibrated IoT sensors, distributed processing within a Lakehouse
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, purchasing, and NU facilities. Proficiency in programming, including Arduino, Raspberry PI, and some circuit design and sensor selection. Knowledge and skills required are normally obtained through vocational
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field trials using sensors for automated mosquito classification; • Morphological identification and processing of mosquitoes, including pathogen screening within the scope of the REVIVE programme and