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Field
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challenge meeting this requirement is the simultaneous need for low-power consumption. The main objective of the project is to develop a complete end-to-end high-performance DNN system for on-premise
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Theoretic algorithms of defense, and how those can/should be modified to account for human attacker’s biases. To accomplish this goal, we study attacker’s behavior and create cognitive computational models
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depth knowledge of a specialized field, process, or discipline and may involve organizing and implementing complex research plans, the development of methods of research, testing and data collection
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progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and
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: Machine learning/deep learning model development for biomolecular data analyses and prediction Research Area: Data science and computational chemistry Required Skills: A Ph.D. in relevant field within
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. Responsibilities include (but not limited to): Lead the development of the NC-ARPES technique (hardware, post-processing algorithm, theory, data interpretation) Propose and perform new TR-ARPES studies of quantum
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techniques, and optimal energy management algorithm development for the optimal operation of the microgrid system. Strong knowledge of power electronics, drives, and control is highly preferred. Experience
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and confidence as they digitalize. For more details, please view https://www.ntu.edu.sg/dtc Key Responsibilities: Conduct advanced research in Generative AI, focusing on the design, development, and
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. In this role, you will be part of the research team, working to develop and evaluate privacy-preserved Generative AI algorithms for generating synthetic Personal Identity Information (PII). This aims
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. This project aims to develop scalable, textile-based wearable devices for real-world joint motion tracking, enabling continuous and unobtrusive monitoring of movement in clinical, rehabilitation, and everyday