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Field
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Responsibilities: Research and develop novel ML-based methodologies and algorithms in LLM-empowered Sub-Graph Learning for Large Graph Models. Working closely with other Postdoc/RA/PhD students to discuss the ideas
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successful candidate will primarily work on the development and enhancement of the OASIS model, contributing to new physical parameterisations, numerical algorithms, and/or performance optimisation. They will
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(OpelRT or Typhoon), electrical system design for better efficiency and system resiliency, and energy management algorithm development using MATLAB/Simulink for marine microgrid applications. Knowledge
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frameworks such as COLMAP and Open3D; Ability to develop algorithms for object detection and tracking, 3D reconstruction, and SLAM. Advanced Control and Intelligent RoboticsSolid knowledge of classical and
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publication, conferences, and/or software distribution. Fellows receive a generous travel and research budget, and have access to the institute's powerful scientific computing resources. Tremendous
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for distributed AI training, agentic AI with modeling and simulation, and end-to-end workflow monitoring, profiling, and optimization. Working with quantum simulation tools, including NVIDIA CUDA-Q, to enable
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ethical and security standards. Concept and Algorithm Development: Innovate in data science, machine learning, and AI. Data Analysis and Reporting: Contribute to data analysis, reporting, and publication
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sampling-based and reinforcement learning-based motion planning algorithms for multiple robotic arms in automotive manufacturing, including testing, performance evaluation in both simulation and actual
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Responsibilities: Conducting regular field work to collect seismic data in Indonesia and Singapore. Seismic data processing and analysis. Implement multiscale subsurface imaging and inversion algorithms
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computers”(under the UKRI Guarantee scheme). Topics include: - Quantum many-body dynamics - Quantum algorithms - Quantum-enhanced numerical methods - Quantum machine learning - Tensor Networks - Topological