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Field
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to develop and analyse implementable, fully discrete methods for function approximation, density estimation, and/or time-dependent PDEs or SDEs in high dimensions, with links to UQ and theoretical
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/Qualifications - Automation or applied mathematics background, with a strong interest in physical models and numerical method - Analysis of partial differential equations, variational approach, Bayesian estimation
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difficult to deploy outside large data centres. This PhD project focuses on developing resource-efficient computer vision methods that maintain strong performance while dramatically reducing computation
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-Physical Systems research theme, focused on improving quality of life through cutting-edge technology. The research aims to design context-aware multimodal AI methods to understand and model human behaviours
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methods, focusing on their ability to solve hard problems more efficiently. Finally, selected developed techniques will be proposed for integration into real-world computer vision workflows, generating
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Materialist theories Developing appropriate (design) research methods Project management About the project:Thinking with Things is funded by the Austrian Science Fund (FWF) and will start on January 1, 2026. It
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to quickly quantify the damage to forest plantations after a cyclone or a tropical storm. There is unrealised potential in using multi-modal computer vision methods that synthesis multi-source Earth
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by developing AI methods that improve recognition of rare species while providing reliable measures of uncertainty. Using state-of-the-art computer vision approaches — vision transformers, self
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24 Nov 2025 Job Information Organisation/Company Computer Vision Center Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Spain
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Development of a numerical tool for assessing radon prevention and mitigation methods in energy-efficient new buildings and existing buildings A PhD position is available in the Department of Physics