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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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. 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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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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kidney injury, providing deeper insight into the cellular processes that support renal immune function. Candidates must have a proven record of scientific achievement during graduate and/or postdoctoral