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electrode structures. • Prototyping of the identified structures via stereolithographic 3D printing and advanced textile techniques. • Development of advanced imaging and characterization technologies (X-ray
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and performing laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image
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to female-biased disease along developmental trajectories. Your tasks and responsibilities Design and execute imaging-based high-throughput screening experiments Develop, optimize cellular assays and CRISPR
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characterize forest structure. Remote sensing data, such as images, lidar, and photogrammetric point clouds acquired from drones, aircraft, and satellites, will play a central role in the development
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candidate you will: Collaborate closely with the experimental team that acquires these multiscale data Analyse rat MRI data, including integration with histology and calcium imaging Combine data across
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holders, setting requirements on data quality and measurement conditions. Together with cardiologists, supervisors and colleague PhD students, you will further perform human testing of several prototype
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of the Ph.D. in Physical Engineering and Microtechnology programme and develop their research at the Imaging and Artificial Vision Lab - ImViA. During this period, the candidate will also undertake
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their performance using microplate reader measurements, flow cytometry and fluorescence microscopy, among other techniques. After building and characterizing prototype circuits, you will fine-tune them and connect
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refine multi-BCDI measurement protocols for imaging hybrid protein-mineral structures. (3) Collaborate with experts from ESRF, TUD, and Weizmann Institute, integrating findings into a geometric frustration
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in