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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian We are looking for a Research Fellow to develop high performance and
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and interpretable machine learning systems. The successful candidate will work on projects involving ensemble learning, large-scale data analytics, and high-performance model design, aimed at developing
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with academic researchers and industry engineers to transform research prototypes into deployable, high-performance solutions aligned with industrial requirements. Key responsibilities: Develop and
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. The candidate will collaborate closely with academic researchers and industry engineers to transform research prototypes into deployable, high-performance solutions aligned with industrial requirements. Key
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a team, to ensure proper operation and maintenance of equipment. Job Responsibilities Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related
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posed by traditional compendial methods. Despite RMM having a shorter incubation period, the dependency of RMM on cells, high operator complexity and challenges in integrating process analytical
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to design, analyse, and operate high-power and high-voltage electrical systems, ensuring safe, reliable, and compliant operation across our facilities. The candicate will work closely with the Principal
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to bridge the gap between advanced computational framework and practical medical use cases. The tools and framework developed by the RA will be meticulously adapted to meet the needs of clinicians
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-mode taxonomies). Implement and maintain high-quality research codebases (PyTorch/HF), experiment tracking, and compute workflows (multi-GPU, HPC/cluster), ensuring reproducibility and documentation
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computational algorithms, with attention to robustness, reproducibility, and performance. Solid understanding of computer vision techniques relevant to cellular and subcellular analysis, such as image