17 model-driven-development Fellowship positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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anomaly with different weather conditions, which can be used to develop a data-driven model for storm surge prediction. Data Analysis: Process and analyze climate, ocean wave and coastal data to improve
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a highly motivated Research Fellow/Engineer to join a strategic collaboration with Procter & Gamble (P&G). This project aims to develop next-generation AI technologies for concept-driven video
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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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to design and develop a robust and scalable software system for autonomous agents navigating immersive 3D virtual environments (e.g., Roblox, Minecraft). Implement a parallelized agent-driven framework where
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Vision, Video Understanding, and Multimodal AI. Design AI models for concept-driven video understanding of consumer facial care behaviours. Work with PI and company to develop the AI solution Develop novel
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contextual scenarios. Develop a unified multimodal detection pipeline that integrates video, audio, and text leveraging fine-tuned Vision-Language Models (VLMs) from WP3, supporting zero-shot reasoning and
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background in power systems, energy modelling, or grid optimisation Proficiency in GUI development (e.g. using Python Dash, Tkinter, or web-based frameworks) Experience working with data-driven simulation and
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following areas: Structural steel or aluminium structures Welding, fabrication, or construction automation Experimental structural testing and instrumentation Numerical modelling and simulation AI/data-driven
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, or texturisation methods. Working knowledge of process optimisation tools (e.g. RSM) and familiarity with data‑driven or AI‑assisted modelling approaches is an advantage. Experience in pilot‑scale processing, scale
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, accumulated deformations, and their impact on structural performance, particularly for compression members. Develop data-driven reusability assessment platforms integrating NDT data, machine learning models