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Field
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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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: 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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Responsibilities: The successful applicant will be responsible for: Obtaining theoretical results at the interface of geometry and biophysics Designing, implementing, and testing algorithms to model active matter
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planning algorithms for GPS-denied lunar environments and extreme operational conditions stochastic optimisation frameworks for mission-critical decision-making under uncertainty Research areas and technical
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computational tools for quantifying electromagnetic field distributions down to the fundamental atomic scale. The project will build on recent developments in inverse scattering methods, including ptychography
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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
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to research-based activities, including the development of new data analysis algorithms, processing and analysis of field data, and participation in the fieldwork. Your responsibilities will include: Conduct
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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI