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. Characterise and optimise the algorithm for signal data processing for real-time cell analysis and sorting Develop a user-interface platform for end-user testing of clinical samples. Support lab procurement and
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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. The Research Fellow will be employed and based at NTU, and is expected to travel overseas to collaborate with scientific teams at CEA, France. The holder will: Apply advanced machine learning algorithms
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power system simulation Energy management system (EMS) or supervisory control algorithm development Hardware-in-the-loop (HIL) platforms (e.g., OPAL-RT, Typhoon HIL) Experience in battery energy storage
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progress. Ability and willingness to work some flexible hours. Extensive experience in large-scale pre-training of large language model. Experienced in developing machine learning algorithms and large
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peer-reviewed journals and/or top-tier conferences. Knowledge & Skills: Strong foundation in machine learning, deep learning, and algorithm development. Proficiency in scientific programming (e.g
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international collaborators across clinical, academic, and industry settings to develop privacy-preserving machine learning approaches, federated learning frameworks, and interpretable algorithms for multimodal
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Responsibilities: Design and implement advanced AI/ML models for healthcare applications, including predictive analytics and generative AI solutions. Develop and validate digital phenotyping algorithms using
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for three highly motivated Research Fellow to join Associate Professor Xia Kelin's team at the School of Physical and Mathematical Sciences. The project focuses on developing Mathematical AI techniques
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods