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Postdoctoral Fellow with Professor Morgane Austern. Professor Austern’s group focuses on research in high-dimensional statistics, probability theory, machine learning theory, graph data, Stein method, ergodic
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and data pipelines to enable real-time data acquisition and closed-loop control. Collaborate with AI researchers to implement machine learning models for adaptive experimental design and autonomous
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Location_ONB: Kent Ridge Campus Posting Start Date: 31/10/2025 Job Description The successful candidate will work with Associate Professor Duane Loh on conducting research at the interface of Machine Learning
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digitalization and computation. To further develop machine learning tasks for scent signal classification/fusion. Set up and analyze experiments under different conditions. To propose a methodology/framework in a
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uses cryo-electron microscopy to understand how viral proteins are recognized by antibodies at an atomic level, and how that recognition can be exploited to design effective vaccines. You will learn
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skills
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: PhD degree in Computer Science, Electrical Engineering, or a closely related field Strong research background in computer vision and deep learning Solid experience with multimodal learning, segmentation
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with machine-learning–enhanced statistical inference. This position is based at the University of Otago in Dunedin and will be managed/supervised by Dr Fabien Montiel. The postdoctoral fellow will lead
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performance enhancement. The Postdoctoral Researcher will coordinate and lead a research project at the intersection of wearable sensing, controls, machine learning, AI, robotics, and movement science. They
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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