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in signal representation/processing, esp for scent signals. Prior research experience and track record in signal detection, machine learning and deep learning. Prior programming experience in state
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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communication, or signal processing. Proficiency in programming languages like Python, MATLAB, or C++, and experience with AI/ML frameworks like TensorFlow, PyTorch, or scikit-learn. A proven track record of
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The Neuron Signaling Lab at National University of Singapore is seeking a motivated and skilled Research Fellow to join our interdisciplinary neuroscience team. We use advanced optical imaging and
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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communication skills Commitment to mentoring graduate and undergraduate students Desirable (but not required): Experience with time-series QA datasets (e.g., Time-MQA, TSQA, MTBench) Background in signal processing
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: Develop novel machine learning theories and techniques for analyzing noisy time-series data, with a particular focus on seismic signals Perform uncertainty quantification in time-series analysis to assess
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the term of their appointment. In addition to annual leave, the Fellow may apply for leave to undertake research and fieldwork overseas, subject to the approval of the CIL Director. Application Procedure
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Singapore. Key Responsibilities: Collect data and signal processing Assist both lab and field tests of Key responsibility 4 (Write proposals for further development) Publish papers in top journals Write
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Computer Science, Electrical & Electronic Engineering, or equivalent. Background knowledge in signal representation/processing, data-driven and machine learning/analysis, esp in climate related topics. Prior