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approaches, machine learning) where appropriate. The successful candidate will actively promote FAIR data practices and will have opportunities to contribute to teaching, training, and wider community
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tools such as R, Python, or MATLAB as well as relevant machine learning frameworks Experience in statistical data analysis, and expertise in areas such as experimental design, linear/nonlinear models
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looking for your next challenge? Do you have a background in machine learning or fluid dynamics and an interest in applying your skills to understand the dynamics of Earth’s fluid core and space-weather
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challenges from low carbon shipping and sustainable fuels to solar power technologies and advanced brain models. Learn more at https://mecheng.ucl.ac.uk . Within this dynamic environment, the Moazen Lab is
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of remote sensing data using physical, statistical and/or machine learning approaches Knowledge of the latest remote sensing techniques, key satellite missions (e.g. Copernicus) and their application
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Radio Frequency (RF) Systems: Extensive knowledge on network management and control Software Defined Radio (SDR): Data Analysis and Processing Programming and Software Development AI/Machine Learning (AI
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Programming and Software Development AI/Machine Learning (AI/ML): Research and Publication Additional information For informal queries, please contact: Professor Dimitra Simeonidou: Dimitra.Simeonidou
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engineering, including machine learning, sustainable construction, climate adaptation, and intelligent tools. Demonstrate future contributions to capacity-building and socio-economic advancement after
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proven interest in AI foundations and its application in civil and environmental engineering, including machine learning, sustainable construction, climate adaptation, and intelligent tools. Demonstrate
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conditions. The researcher will also work with team members within the consortium in generating necessary data required for developing a machine learning model for storm surge prediction. Key Responsibilities