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learning, image/audio processing
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to: Contribute to development and deployment of particle imaging systems for use in breaking waves, both in the field and in the lab Contribute to analysis of images, and development of the open-source analysis
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and technology; sexual and gender-based violence; image-based sexual abuse; technology-facilitated violence, including AI-Facilitated harms. You will have a PhD and a strong research record in Media
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, working closely with other project participants on field measurements, laboratory work and model development. The candidate will be expected to: Contribute to development and deployment of particle imaging
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insurance, supported by INESC TEC. 2. OBJECTIVES: • Research novel deep learning models for anatomically structured EGGIM estimation.; • Develop methods for image-level and examination-level reliability
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Python. Hands-on experience with: PyTorch Hugging Face Transformers OpenCV Experience working with deep learning models for image or video analysis.
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biology, chemical biology, nutrient sensing, pharmacology, CRISPR genetics, quantitative biochemical and imaging-based readouts, and omics-based profiling, potentially including metabolomics, proteomics
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independent research projects focused on the somatosensory system Conduct experiments in mice and rat models, including electrophysiology, live imaging, and behavioral studies Apply molecular biology techniques
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) learning numerical methods for wave-equation-based processing, imaging, and inversion. Wave phenomena are ubiquitous in science, and they extend to objectives ranging from global Earth discovery, to natural
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and interpret experiments using cell line models of epithelial and lymphoid malignancies. Apply quantitative microscopy and histopathological imaging techniques to investigate immune modulation pathways