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transcriptomics data analysis. Experience in quantitative image analysis, computer vision, or digital pathology. A strong background in cancer biology or immunology. Experience with machine learning, deep learning
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to reconstruct subsurface defects; Implement image/signal‑processing or machine‑learning pipelines for automated flaw characterisation; Collaborate with the Federal University of Rio de Janeiro, including short
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computer vision and machine learning approaches to integrate ground-based imagery, remote sensing data, and lidar data for high-resolution flood detection and mapping. Develop and calibrate hydraulic flood
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Learning and Deep Learning libraries (e.g., Pytorch, Tensorflow) will be considered a significant advantage; Previous experience in image processing and\or computer vision will be considered an advantage
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instruments and high throughput genomics that informs advanced numerical analysis methods (modeling, statistics, machine learning). Plankton encompasses all organisms roaming with marine currents. Those
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the outcomes of SCC surgery. Job Responsibilities: As a PhD candidate, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and healthy tissues using both
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https://www.academictransfer.com/en/jobs/354348/postdoc-position-on-ai-based-tr… Requirements Specific Requirements PhD in a relevant field (e.g., medical imaging, computer vision, AI) Expertise in
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this suits a candidate with a background in optical systems / imaging, or with more experience in machine vision, or systems control and automation, or data interpretation. A candidate would not be expected
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in solid mechanics framework Experience in non-linear solid material response and fracture modeling Experience in machine-learning modeling for solid mechanics applications Experience in
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delineation and improve the outcomes of SCC surgery. Job Responsibilities: As a PhD candidate, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and