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configurations hinders the creation of generalizable solutions for processing these images. This project proposes an innovative approach that combines state-of-the-art diffusion models with physical radar
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fundamental radar wave propagation equations into the diffusion process, allowing for more accurate and physically consistent image restoration. The developed framework will be able to transfer knowledge
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dissection, and image and illustration editing, as well as experience and availability for fieldwork. Applications should be sent to einicker@usp.br by 15 February 2026, including a motivation letter, one
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. The fellowship candidate must hold a Ph.D. in Agricultural Engineering or related fields, with expertise in irrigation, remote sensing, image processing, and precision agriculture. Experience in programming
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. Duration The fellowship is granted for 36 months. 4. Eligibility and Requirements • PhD obtained within the last 4 years or by May 31st; • Background in IR image analysis and experimental phase change
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expertise in advanced immunology, histology, flow cytometry, confocal microscopy and image analysis techniques. Experience in different national and international laboratories is a positive aspect to be
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expertise in advanced immunology, histology, flow cytometry, confocal microscopy and image analysis techniques. Experience in different national and international laboratories is a positive aspect to be
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identifying systemic events in the Brazilian Interconnected Power System (SIN). In addition, the project proposes the development of a processing and graphical visualization platform based on Grafana, enabling
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-processes/ More information about the fellowship is at: fapesp.br/oportunidades/8962 . Where to apply Website http://www.fapesp.br/oportunidades/8962 Requirements Additional Information Eligibility criteria
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to staff position within a Research Infrastructure? No Offer Description The Laboratory for High-Pressure Technology and Natural Products (LTAPPN/ZEA) and the Equine Clinical Practice, Surgery and