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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
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computing. With extensive experience in medical image analysis, computer vision, and AI systems through collaborations with leading institutions. Key Responsibilities: Conduct advanced research in the areas
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dedicated to technology such as state-of-the-art light microscopy, nano- and micro- fabrication, and computing. We are seeking a Research Fellow with expertise in transmission electron microscopy (TEM
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cilia and nuclear signaling in the brain. Position Summary: We seek a candidate with strong expertise in microscopy and computational image analysis to: Support and enhance ongoing imaging projects in
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from the Department of Civil and Environmental Engineering. This position is part of an exciting research programme aimed at advancing the multi-robotic wire-arc directed energy deposition technology and
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bioengineering, aquaculture systems, and computer vision. Job Requirements: PhD or Senior Scientist in Bioengineering, Computer Vision, Environmental Technology, Biomedical Engineering, Aquatic Biology, or a
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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
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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
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. Write the report for the project progress. Work with research assistant for the prototype. Job Requirements: PhD in Electrical and Electronic Engineering, Computer Engineering / Science, or related field
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Engineering field in computer science, or related field. Strong expertise in natural language processing (NLP) and large language models (LLM) Over 1-year research experience in the above required areas