421 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S"-"U.S" positions at Nanyang Technological University
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operations, such as data storage, budgets, expenses, assets, and ethics approvals. Key Responsibilities: Conduct independent and collaborative research applying AI and machine learning techniques
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Computer Engineering, Computer Science, or a related field from a prestigious institution. Extensive experience in deep learning, AI, computer vision, 3D reconstruction algorithms, and large-scale Pre
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frameworks for advanced property prediction and analysis of inorganic disordered materials. Carry out machine-learning based first-principle calculations aimed at advancing the understanding defect-based
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deployment enabling validation and demonstration of real-world applications. We are looking for a software engineer to develop and maintain scalable software applications with a focus on AI, machine learning
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delegated by PI Job Requirements Master qualification degree in Electronic Engineering or Computer Science Familiarity with pinching antennas and machine learning Good written and oral communication skills
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related discipline. You must be a current machine learning, theory and atomistic simulations for material design. You must be an excellent communicator in English, both verbally and written. You must be
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topics ranging across programming language (especially Bayesian statistical probabilistic programming), statistical machine learning, generative AI, and AI Safety. Key Responsibilities: Manage own academic
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at NTU. Key Responsibilities: The successful applicant will be responsible for Obtaining rigorous mathematical results geometric optimization and applications to data science and machine learning Designing
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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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: 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