55 algorithm-sensor-"Newcastle-University" Fellowship positions at Nanyang Technological University
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the development of integrated sensor arrays through innovative materials design and validation techniques. This role supports NTU’s strategic direction in cutting-edge sensor research by contributing
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Developing and integrating AI algorithms into the real development progress Preparing academic publications such as patent applications and research papers Contributing to quarterly and annual report writing
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a Research Fellow to contribute to a project focused on algorithm design in Game Theory and Fair Division. Key Responsibilities: Formulate mathematical models for research problems in computational
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and RISC-V architectures. Investigate various aspects of system design, including: Topology exploration, routing algorithms, protocol and flow control design Chiplet oriented and interposer design
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architectures. Investigate various aspects of system design, including: Topology exploration, routing algorithms, protocol and flow control design Chiplet oriented and interposer design strategies, SiP and
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state-of-the-art facilities to work on the following: Developing advanced path planning, search, and exploration algorithms for multi-UAVs systems in unknown and complex 3D environments. Designing
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. The roles of this position include: Development of algorithms to improve memory/sample/time efficiency of LLM training. Development of a workable prototype system with capabilities such as conversational
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noise, allowing only specific algorithms with relatively shallow quantum circuits to be executed. In the NISQ era, hybrid algorithms run partially on quantum computers and partially on classical computers
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. The successful candidate will play a pivotal role in a project centered around variational quantum algorithm in the near-term, especially on innovating advanced error mitigation or detection techniques to solve
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems