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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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Number of Positions: 1 Eligibility: UK Only Funding: School of Computer Science Scholarship, in support of the EPSRC Grant: Mixed precision in Krylov Methods, providing the award of full academic
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educational programs in both Computing Science and Informatics, we are now seeking a doctoral candidate with a focus on AI models and policy applications for climate risk communication. This position is a
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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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Description Where: At the Chair for Computational and Theoretical Biology ( CCTB ) and the Center for Artificial Intelligence and Data Science ( CAIDAS ) of the University of Würzburg. Project
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the science of battery modelling, state estimation, fault diagnosis and control by developing the intelligent battery management systems that will make energy storage safer, more efficient, and longer-lasting
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27.10.2025, Wissenschaftliches Personal Are you passionate about generative AI and digital twins for intelligent mobility systems? Do you see potential in using large language models, vision
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This PhD project focuses on advancing computer vision and edge-AI technology for real-time marine monitoring. In collaboration with CEFAS (the Centre for Environment, Fisheries, and Aquaculture
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through the EU Research Framework Programme? Not funded by a EU programme Reference Number E06_X256 Is the Job related to staff position within a Research Infrastructure? No Offer Description AIoT On-Board
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combining physical models, sensor data, computational methods, and damage and fracture mechanics concepts to create a virtual replica of the composite tank, enabling predictive maintenance, lifetime