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on the development, optimization, and clinical evaluation of new x-ray-based imaging methods. The lab focuses on the use of medical physics approaches to improve image acquisition methods and processing algorithms
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: In higher eukaryotes, proteins that lack an apparent folded structure are enriched in many vital processes. The Lemke group studies intrinsically disordered proteins in vital cellular processes
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team and has basic experience in hands-on lab work and in data analysis. Prior experience in optical imaging, nanofabrication, data processing is highly valued but not mandatory. We offer We
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is to investigate localized flow and crystallization processes of PCMs in devices under different conditions with advanced 3D imaging tools like CT and NMR imaging, and to couple this with performance
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of vision, embedded electronics, signal and image processing for the joint development of imaging systems and associated methods. Particular emphasis is put on the design of unconventional and multimodal
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computational research. In particular: • A high-quality imaging platform • A dedicated biocomputing hub that guarantees reliable data storage, management, and advanced analytical capacity. Our laboratory is
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. Identify the key factor affecting texturization processes and study the relationship between food structure and textural characteristics at different scales using spectroscopic, microscopic, rheological
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characterizing defects such as dislocations Applying generative models (e.g., GANs, diffusion models) to augment microscopy datasets Investigating domain adaptation techniques across different imaging modalities
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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. Machines must be equipped in-situ with smart sensors and supported by systems that can process such as images and time series, in real time. Machine learning and AI have become essential for driving