20 model-checking Fellowship research jobs at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) in United Kingdom
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-A_Tranche-2-Research-Projects-Awarded-Under-CFI-Singapore.pdf ). The primary role involves developing and validating Hydrodynamic models to study performance of integrated floating breakwater and marine
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that are relevant to industry demands while working on research projects in SIT. Job Details This Research Fellow will contribute to the UrEco 2030+ project: “Optimizing Urban Ecosystem Services Model for Urban
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strategic research project on full electric harbour craft microgrid modelling, onboard energy management systems (EMS), and hardware-in-the-loop (HIL) validation. The Research Staff will contribute
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in the development, validation, and optimization of 3D-printed Ship Hull and Connector System. This includes conducting finite element modeling, ship resistance and stability assessments, as
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and trigger diverse contextual scenarios. Develop a unified multimodal detection pipeline that integrates video, audio, and text leveraging fine-tuned Vision-Language Models (VLMs) from WP3, supporting
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should have relevant competence in the areas of processing technology, physical and structural analysis, material formulation, and mathmatical modeling. The candidate should also have a PhD or other
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the research team under the project titled: Occupant Tenability and Time to Flashover in Small-Sized Flats (Numerical Study Phase) Under this job, you will develop a CFD modelling platform to study effects
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the microgrid model and validate performance under different simulated conditions. Conduct testing of control strategies under various operating conditions such as extreme weather, load variation, equipment
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/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related disciplines. Knowledge of autonomous vehicles or cyber security will be
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narratives) Leverage fine-tuned Vision-Language Models (VLMs) for game scenario detection, supporting zero-shot reasoning and scene-graph inference. Ensure the system is deployment-ready by supporting