21 model-checking Fellowship positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) in Singapore
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, and research team to ensure timely achievement of project deliverables. Undertake the following specific responsibilities in the project: i. Develop, train, and optimise deep learning models for object
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to the UrEco 2030+ project: “Optimizing Urban Ecosystem Services Model for Urban Climate and Biodiversity in Singapore towards 2030 and Beyond.” This position requires experience in Geographic Information
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text leveraging fine-tuned Vision-Language Models (VLMs) from WP3, supporting zero-shot reasoning and scene-graph inference. Ensure the system is deployment-ready by supporting benchmarking of inference
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impactful, application-driven research. This position supports a strategic research project on full electric harbour craft microgrid modelling, onboard energy management systems (EMS), and hardware-in
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. This includes conducting finite element modeling, ship resistance and stability assessments, as well as overseeing AM process and reporting. The role also involves designing and validating connectors
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and reliable solution can be technically demanding. Complexity of Ship Systems Ship systems are large-scale, interconnected, and subject to complex operating conditions. Accurately modelling failure
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. This includes conducting finite element modeling, ship resistance and stability assessments, as well as overseeing AM process and reporting. The role also involves designing and validating connectors
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to the UrEco 2030+ project: “Optimizing Urban Ecosystem Services Model for Urban Climate and Biodiversity in Singapore towards 2030 and Beyond.” This position requires experience in Geographic Information
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acousto-structural transmission paths, developing predictive models, and producing research outputs that support practical noise mitigation solutions for the built environment industry. Key Responsibilities
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Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related