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Engineering Employee Category: Research Staff Location: Kent Ridge Campus Posted On: 22/04/2026 ▲ Collapse Job Title: Research Fellow (VIO/LIO & State Estimation) University-Level Unit: College of Design and
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Do you have a strong technical background in Machine Learning and Numerical Modelling? Are you interested in working with industry to develop Machine Learning methodologies and protocols needed
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, trace element and isotope micro-mapping and spot/traverse analyses (fs-LIBS, Vitesse-TOF-ICP-MS, and Neoma-LA-MS/MS-MC-ICP-MS) to quantify spatial and temporal variations of fluid properties with respect
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project - “STF -automotive component data- driven and real-time predictive universal vehicle self-diagnosis system”. Qualifications Applicants should have: (a) a doctoral degree in Mechanical Engineering
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Digital Twin Framework for Smart and Sustainable Advanced Manufacturing Research area 3: Advanced Multifunctional Materials The ideal candidates would have a background in machine learning, manufacturing
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Materials Development for Sustainable Rare Earth Element Recovery Using Electrodialysis (AI-REE) Project Introduction: This project focuses on developing sustainable and cost-effective technologies for rare
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for light–matter interaction in hyperuniform disordered plasmonic structures, including electromagnetic modelling, optimisation of metal–dielectric–metal resonators, and physics-informed machine-learning
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would have a background in machine learning, manufacturing, characterization, and testing of novel high performance multifunctional materials. During the project, you will conduct independent research
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-driven reusability assessment platforms integrating NDT data, machine learning models, and RFID-enabled traceability systems. Prepare and draft technical reports, conference/journal papers, and
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the development of an independent research profile. The purpose of this role is to: Contribute and lead elements of mixed-methods research across ARC South West projects, including study design, delivery, and