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Field
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deep-learning and 3D computer-vision models that detect features while representing a distribution of plausible interpretations. Encode geological relationships in a knowledge graph that stores
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, and regenerative constructs. The project combines advanced 2D and 3D bioimaging, including micro/nanoCT, confocal microscopy and SEM, with computational image analysis, computer vision and machine
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integrates cancer biology with engineered tumor microenvironment models and quantitative imaging. Research may involve human head and neck or breast cancer models, fibroblasts, immune populations, 2D/3D cell
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-qualification Required Qualifications Bachelor's degree in a relevant field Degree or formal training in 3D Modeling, 3D Animation, Medical Visualization, Computer Graphics, or a related discipline. Additional
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understanding with language-based reasoning. Process micro-facial expression data more efficiently in computer vision and vision language models. Create a language-guided representation for subtle facial motion
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 2 months ago
for use in research, film, virtual reality, biology and medicine. Using unique 3D & 4D capture facilities, machine learning, computer vision and advanced graphics, we are modeling every nuance of how humans
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Strategic Principles and has three critical components; patient care, education and research that together enhance our contribution to society. Job Summary Michigan Medicine's Radiology 3D Imaging Lab is
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level Basic knowledge in at least one of the following areas: computer graphics, computer vision, or machine learning / neural networks Programming experience in Python; knowledge of PyTorch is a plus
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. The research combines robotics, computer vision, artificial intelligence, machine learning, control systems, and medical robotics to solve one of the most challenging problems in modern automation. Project
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Overview We are seeking a Grade 7 Research Associate in Computer Science for a two-year post within CAPTURE-PH, a multi-centre programme using chest CT and artificial intelligence (AI) to improve