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: Physics-informed neural networks (PINNs) & surrogate modelling Time-series modelling & anomaly detection Bayesian methods & uncertainty quantification LLMs & multi-modal models Graph neural networks (GNNs
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for the duration of the scheme. Application Process Applications are open throughout the year. Applications received before 15 January 2026 will be considered for intake 2026. Interview by
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psychology, neuropsychology, neurology, psychiatry, cognitive neuroscience, electrical engineering, biomedical engineering, computer science, physics or related fields). A PhD* (or equivalent research
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areas: Computer Vision and Image Processing Machine Learning, Deep Learning, and Reinforcement Learning Large Language Models (LLMs) and Multimodal Models Generative AI, Agentic AI, Physical AI, and
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Engineering or related disciplines. Priority skill areas include: process monitoring and control, industry 4.0, modeling, AI and ML applications for the process industries with particular emphasis on delivering
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, process optimization and food characterization. Key Responsibilities Lead bench formulation of mushroom‑based and plant‑based food products, especially focusing on muscle‑like architectures to achieve
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. Support the design and development of physical products from early concept through to final production Present designs to customers, develop and iterate designs through sketches, prototypes, renderings and
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for organisational transition, focusing on but not limited to caregiver workload reduction, care-process redesign, adoption planning and care automation support. Support healthcare innovation projects by coordinating
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-term awardees will have a service commitment of 1 year for every year of sponsorship. Application Process Applications are open throughout the year. Applications received before 15 January 2026 will be
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modelling using Delt3D software. The role of the researcher is to perform physics-based modeling to build a numerical model that can predict storm surges in Singapore coastlines based on different weather