46 machine-learning-"https:" "https:" "https:" "https:" positions at Nanyang Technological University
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creating original computer-generated imagery to explore how lighting and rendering shape the emotional ambience of a scene. This learning forms the foundation for further studies in Visual Effects and 3D
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning
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Develop instrumentation and fixtures for the automation. Capabilities in advanced finite element or machine learning tools for process optimisation Disseminate the research outcomes into Journal
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Assistant to carry
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-driven Design Automation for Advanced Packaging to develop and integrate artificial intelligence methodologies into advanced packaging electrical design. The role will focus on leveraging machine learning
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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the end-to-end discovery process, including data preparation, statistical analysis, and methods for extracting meaningful insights from large datasets. Core machine learning techniques such as decision tree
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Engineering, or related field. Research experience with Artificial Intelligence/Machine Learning/Large Language Model. Publication track record in a series of top tier conference papers e..g, in NeuRIPS, ICLR
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for energy saving purpose. The role will focus on geometric representation, multi-physics numerical simulations, machine learning and manufacturability constrained design optimization given metal additive