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Field
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modeling. Proficiency in Python and experience with AI/ML frameworks such as PyTorch or TensorFlow. Experience handling large geospatial, atmospheric, or remote sensing datasets is preferred. Strong
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models ranging from baseline approaches to graph neural networks. You will also oversee the open release of project datasets, models, code and documentation. The successful candidate will join Oxford's
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that produce, validate, analyze, and deliver shallow-water bathymetry and related coastal geospatial data products. The position leads the design and maintenance of scalable, automated data-processing workflows
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positively Experience with multimodal learning, representation learning, self-supervised learning, or foundation models. Experience with geospatial, remote sensing, and citizen science datasets. Experience
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 17 days ago
inform representations and encoder adaptations. This activity will provide hands-on experience in making three-dimensional vegetation structure accessible within data-driven geospatial modeling processes
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description In this EngD project, you will develop an AI model that automatically
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start date. Preferred Qualifications: Research experience in computer vision, NLP, geospatial data systems, or high-performance computing. Brief Description of Duties: The Postdoctoral Associate will
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Vacancies EngD position: AI for Underground Infrastructure Detection and Characterisation Key takeaways In this EngD project, you will develop an AI model that automatically detects underground
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investigate how spatial development interacts with systemic dynamics and implementation feasibility. Using geospatial modeling, participative mapping, and interactive workshops, you will analyze how landscape
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people’s interactions with the natural world and consequences for human wellbeing. MGeo advances and deploys cutting-edge methods, models and technologies in environmental science, quaternary sciences