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resulting precipitation and extreme weather. We study global and regional climate change and are at the core of international community climate modeling efforts that also involve AI and Machine Learning. We
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programming, algorithm development and deep learning model implementation, and practical experience in drone and boat-based surveys are preferred. Background Investigation Statement: Prior to hiring, the final
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climate change - Computer vision, e.g., colour vision, human colour vision, colour appearance models, etc. - AI technology, e.g. statistical learning, neural network learning, deep and transfer learning
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Develop instrumentation and fixtures for the automation. Capabilities in advanced finite element or machine learning tools for process optimisation Disseminate the research outcomes into Journal
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applications for PhD research fellowship position(s) within the field of machine learning, AI Safety, and mechanistic interpretability, to be filled earliest by 1 January 2026 for a period of three years
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Responsibilities: To perform pioneer research in scent digitalization and computation. To further develop machine learning tasks for scent signal classification/fusion. Set up and analyze experiments under different
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Job Description The Centre for Machine Learning within the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark
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by integrating petrophysics, rock physics, geophysics, geomechanics and machine learning. A detailed project plan will be developed in collaboration with the successful candidate at the start of PhD
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research proposals and reports. Job Requirements Possess a PhD degree obtained in a related discipline (transportation engineering, operations research, computer engineering/science, or related disciplines
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worked in MRI research previously or have strong computational / AI / machine learning skills used in other areas of research. Essential criteria PhD qualified in relevant subject area Ability to work as