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), or biological sensors (sweating, ECG, etc.). These scenarios raise new scientific challenges, both in terms of modeling (intermodal alignment, joint representation, generation control) and in terms of usage
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. With more than 70 years of history, PPPL is a leader in the science and engineering behind the development of fusion energy, a potentially limitless energy source. PPPL is also using its expertise
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for Digital Twin Earth (AI4DTE). The main goal of DTEClimate project is to maximize the information extracted from EO data by extracting sensor information and generating actionable, uniform, accurate, complete
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, the research group is seeking a new colleague to support the design of an enhanced framework that integrates high-level task sequencing with low-level sensor-fusion control to facilitate in-process adaptation
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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 sciences
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-of-need. The recently funded project (https://cepi.net/transatlantic-scientists-transition-traditional-vaccinedevelopment-rapid-response-platform-faster) marries engineering method-side innovation with cell
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bed fusion (LPBF) using multi-phase melt-pool physics and high-fidelity simulations. Main duties and responsibilities Use a modelling approach which allows the creation of a virtual qualification
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and/or millimeter-wave measurements. Knowledge of using AI/ML tools and approaches to analyze data. Knowledge of computer vision and sensor fusion techniques. Any understanding or interest in radio wave
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on applying computer vision, machine learning, and sensor fusion to automatically detect, classify, and localize defects, improving the scalability and reliability of building inspection. Research on 3D
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Associate/Full Professor applications in the area of autonomy and robotics, with particular emphasis on computer vision, sensor fusion, and intelligent decision-making. The successful candidate is expected