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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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researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
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Engineering, Mechatronics, etc. Strong background in end-to-end autonomous driving, foundation models and reinforcement learning. Candidates having relevant research or working experience in autonomous driving
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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experience in data-knowledge fusion-driven dynamic modeling of complex structures, specializing in uncertainty quantification of nonlinear systems and intelligent model order reduction methods, with at least
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Biotechnology and Bioprocesses, Membrane Technology, Chemicals and Materials, Resource Recovery, and Modeling & Artificial Intelligence. By harnessing its cross-cutting, interdisciplinary, and transformative
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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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quantum sensing technologies (e.g., Rydberg atomic sensors) for wireless communications and sensing. Key Responsibilities: Develop quantum-related theories, models, and algorithms for various communications
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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integration and AI models tailored for fish behaviour, health, and stress signal analysis. Investigate and apply novel machine learning and deep learning techniques for pattern recognition, classification, and