46 machine-learning "https:" "https:" "https:" "https:" positions at Nanyang Technological University
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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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and predictions. Use cutting-edge methodologies such as A.I. and machine-learning to accelerate the numerical simulation processes. Develop optimal control strategies for energy systems Publish high
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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
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degree in Signal Processing, Machine Learning, Information Engineering, Applied Mathematics, Information Science, or other related majors is required. Consideration will also be given to candidates who
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to validate theoretical approaches, utilizing machine learning techniques to derive meaningful conclusions. Collaborative Projects: Engage in collaborative research with interdisciplinary teams, contributing
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Project Officer (Civil Engineering/Materials Science/Mechanical Engineering/Construction Technology)
, mechanical testing, mix design preparation). Familiarity with AI or data-driven tools, such as: machine learning for prediction/modelling, data analytics for material/printing optimisation, or AI-assisted
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to apply as Part-Time Lecturer for Enterprise Network Design. The Part-time Lecturer is expected to teach an undergraduate elective course commencing in January 2026. This 13-week course is a specialized