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Field
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successful candidate is required to: • Contribute to Robust Splatting, Dialogue, Speech Signal Processing and Machine Learning algorithms. • Contribute to Image Processing and Machine Learning algorithms
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geophysical survey and machine learning algorithms. Mainly responsible for processing geophysical/geomechanical data and analysing the data using machine learning. Conducting research, supervising undergraduate
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to the implementation and characterisation of AI/ML algorithms for 6G integrated sensing and communications systems, with particular emphasis on embedded platforms, digital processing architectures, efficient
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to publications in top-tier international conferences and journals, as well as real-world implementations. The role includes designing novel algorithms, building robust software systems, and collaborating with
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support the development, simulation, testing, and implementation of collaborative control algorithms for multi-agent robotic systems, under the guidance of the PI and senior researchers. The work will first
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novel algorithms for efficient, high-fidelity 3D scene reconstruction and representation, including applications in embodied environments where an agent must continuously perceive, update, and reason
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multiple radar units into autonomous vehicle platforms and evaluate perception algorithms in diverse scenarios. The successful candidate will work closely with our industrial partners and will analyse
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About the Opportunity Conduct research on machine learning, control theory, and synthetic biology. The work will combine tools from dynamical systems, control theory, and the theory of algorithms
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implement VLA models and world models. Develop and optimize deep learning algorithms to enable robotic arms to perform complex tasks guided by natural language instructions. Utilize PyTorch to train and fine
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technical elements of computational astrophysics research, which may include but are not limited to: algorithm and software development; application or development of computational or statistical methods