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implement algorithms for image processing and analysis of multisensor data (RGB, LiDAR, hyperspectral). Design and implement explainable AI (XAI) models for the detection and quantification of grape berry
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successful candidate should have excellent study results and a strong background in mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
technologies to scientific research study and experiment design, big data mining and processing, algorithm development, and complex computational analysis. They have expertise in the ethical issues of using AI
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practice while supporting complex tasks such as image and video enhancement, layered editing, and object-level content manipulation. The candidate will contribute to 1) algorithmic development, including
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automation and simulation-driven optimization of high-frequency systems using machine learning * development of optimization algorithms and numerical modeling procedures * development of simulation models
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Scientist Salary range: See Table 37-B [https://www.ucop.edu/academic-personnel-programs/_files/2025-26/represented-july-2025-scales/t37-b.pdf ] for the salary range for this position. A reasonable estimate
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Geometry, Statistical Learning Theory, Statistical Inference, and Information Geometry. (2) Computing for AI: Programming Language Theory, Algorithm Theory, Combinatorics, Optimization Theory, and
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(OpelRT or Typhoon), electrical system design for better efficiency and system resiliency, and energy management algorithm development using MATLAB/Simulink for marine microgrid applications. Knowledge
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Reference Number AE2025-0526 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0526.pdf CALL FOR
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in medical image analysis. The ideal profile should demonstrate experience in developing deep learning algorithms applied to radiological imaging, particularly in breast and thoracic domains. Knowledge