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Field
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manipulated or synthesised images, audio and video data, often called DeepFakes. This fact is a serious threat to the trustworthiness of news in the media and forensic processes in criminal investigations
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, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision, digital pathology, whole-slide image analysis, self-supervised learning, foundation models, multiple
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data, including Digital Image Correlation (DIC/DVC) and three-dimensional image analysis. Generation and exploitation of digital models based on experimentally acquired geometries. Scientific programming
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! Collaborate on impactful research in memory and task-based functional imaging (fMRI). PhD-fellowship Apply for this job See advertisement About the position A 3-year position as Ph.D. Research Fellow is
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computational image analysis, computer vision and machine learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties to biomaterial performance and
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integrating AI with vision at the edge. Despite recent advancements, the synergy between AI and computer vision remains constrained by fundamental imaging bottlenecks. Conventional HDR techniques frequently
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further. Another direction of the project will be to investigate the interplay between standard digital implementations of the approximate quantum optimization algorithm (QAOA) and analogous continuous time
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software stack, and quantum artificial intelligence. The aim is to pioneer quantum software technologies with real-world relevance by developing the necessary foundations, implementing them in prototype
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) develops and applies innovative molecular imaging technologies that reveal biological processes across multiple spatial scales—from whole organs to individual cells and subcellular structures. Within
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advanced 2D and 3D bioimaging, including micro/nanoCT, confocal microscopy and SEM, with computational image analysis, computer vision and machine learning. The aim is to develop robust and standardized