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vivo experiments to investigate retinal neurovascular dynamics using the AO-RSO system; Developing or adapting high-speed image acquisition and processing methods for the simultaneous extraction
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(EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With ICT present in almost every device and product we use
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into clinical applications (and vice versa). The School consists of eight research departments: Cardiovascular Imaging, Cancer Imaging, Early Life Imaging, Imaging Chemistry & Biology, Biomedical Computing
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for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field strong background in image processing and analysis, including deep learning
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of motion analysis in collaboration processing of images in preparation for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field
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, or Mechanical Engineering. Experience in microfluidics and fluid mechanics. Strong programming skills in MATLAB. Experience with a Verasonics ultrasound imaging system is a plus. Good communication and
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proficient with computer software including MicroSoft Office, Adobe Acrobat and Excel database software. Desirable Qualifications: Experience with statistical software (e.g., Graphpad/Prism, SPSS, STATA, R
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and setup: Within the project, we follow a multidisciplinary collaborative approach for which we are have recruited 3 PhD students focusing on material science, advanced in vivo imaging and computation
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to self-supervised learning, medical imaging, and population-level phenotyping. About You You will have or be close to the completion of a relevant PhD/DPhil (e.g. in Computer Science, Engineering, or
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in physics or engineering including wave physics and signal processing Expertise in flow quantification and mapping with ultrasound imaging mandatory Extensive experience in programming (Matlab and C