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University of California, Los Angeles | Los Angeles, California | United States | about 17 hours ago
filled. Position description The UCLA Abdominal Imaging / Cross Sectional Interventional Radiology fellowship program provides unique advanced clinically rigorous training in Abdominal Imaging, Image
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will also support the development of behavioural coding approaches for social interaction and strategic decision-making. The role will additionally involve conducting literature reviews and contributing
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quantitative image-analysis approaches for particle tracking, membrane dynamics, and intracellular transport. Analyse experimental data, review relevant literature, and prepare manuscripts for
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microscopy image analysis and spatial transcriptomics to link molecular signatures with tissue architecture. Develop predictive models for disease diagnosis, prognosis, and therapeutic targeting
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with insufficient contrast Link text Identifies links that may be confusing when read by a screen reader Labels Identifies inputs with missing labels Image alt-text Annotates images without alt text
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country-based research teams to develop interview guides, undertake data analysis, coding, and document analysis, and contribute to the development and management of the project's dataset. The role is
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element library FeNiCS, cardiac finite element modeling, medical image processing, and machine learning. The candidate is expected to possess excellent communication and written skills. Additionally
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EEG data. The post-holder will also support the development of behavioural coding approaches for social interaction and strategic decision-making. The role will additionally involve conducting
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University of California, San Francisco Colitis Center | San Francisco, California | United States | about 1 month ago
What is your email address? required Your CV required Your file must be a .doc, .pdf, .docx, or .rtf. No larger than 1MB Selected file: Crop image Remove file Close Edit image On this element you can
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imaging science or related field or an equivalent qualification; (ii) demonstrate research skills in imaging science and machine learning, particularly on image reverse engineering, fake image and