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image sequences. As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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Position Description The Unsteady Flow Diagnostics Laboratory (UNFoLD) led by Prof. Karen Mulleners at EPFL in Lausanne is looking for multiple PhD students to join the group in the fall of 2025 or early
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involve leveraging advanced natural language processing and medical image analysis to transform imaging data into clinically relevant information. Additionally, it will explore the use of multimodal fusion
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
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At the Faculty of Engineering and Science, Department of Materials and Production a position as PhD stipend in Muscle Neuromechanics and Ultrasound Imaging, within the doctoral programme Materials
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Company description The Lab for NanoBiology (Prof. Dedecker) is an interdisciplinary research group focused on the study and visualization of molecular processes occurring in biosystems. We combine
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*. * The Employment Equity Act, which is under review, uses the terminology Aboriginal peoples and visible minorities. Candidates are asked to self-declare when applying to this hiring process. City: Edmonton
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, sports, food safety, and environmental monitoring. By integrating electrochemical techniques and imaging technologies, the unit delivers cutting-edge solutions with real-world impact. Led by Prof. María
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diffusion models usually needs to access a pre-trained model multiple times sequentially to generate high-quality images or videos, which is time-consuming. The training process of diffusion models is also