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Field
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decarbonisation and digitalisation, methodology development and applications Publish findings in top peer-reviewed journals and conference proceedings Collaborate with other researchers on project discussions and
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, train, and validate advanced computational models and machine learning algorithms tailored to complex datasets. Collaborate with multidisciplinary teams including biologists, engineers, and clinicians
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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on AI-driven end-to-end autonomous driving algorithms. Key Responsibilities: The research fellow will be leading the development of AI-driven end-to-end autonomous driving algorithms. The work will
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recommendation mechanisms based on semantic analysis and natural language processing, with the aim of facilitating collaboration and convergence of proposals. Developing and training NLP algorithms in multiple
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: Statistical model development: Led the development of advanced statistical models and machine learning algorithms for forecasting precipitation and temperature in Morocco. This will involve data analysis, model
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Fluid-Structure Interaction to focus on developing computational algorithms for fluid-structure interaction problems including the multiphysics effect of electromagnetism. The Role: As a Research Fellow
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challenges: Successful candidates will contribute to one or more of the following research domains: development of autonomous navigation and path planning algorithms for lunar terrain traversal and regolith
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) Design robust obstacle avoidance algorithms for mobile robots in dynamically changing environments, focusing on formal safety constraints and real-time performance in unpredictable conditions. b) Develop