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for scent signals. Prior research experience and track record in signal detection, machine learning and deep learning. Prior programming experience in state-of-the-art AI techniques. Mastering of a
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of the project. Job Requirements: A PhD degree in mathematics, AI or related areas, with a strong background geometric/topological/algebraic data analysis, geometric/topological deep learning, molecular sciences
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advantage. Solid understanding of algorithm-hardware co-design, especially for robotics or edge AI deployment. Strong programming skills in C, C++, and Python, with experience in deep learning frameworks
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or implementing deep learning approaches on existing clinical systems). Experience and interest in grant writing would be viewed favourably. To be successful in this position, you will have: A PhD in a relevant
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to behavioural and population health data relevant to Singapore’s diverse communities. Develop predictive and explainable machine learning/deep learning/genAI models using multimodal cross-section and longitudinal
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, Medicare and/or commercial claims data, a deep understanding of analytical methods and statistics, and advanced programming skills are therefore desired. The role will also involve preparation of graphical
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and expanding team. You’ll play a key role in our success through your code, publications, and strategic promotion of our work. * PhD in Computer Science, Biomedical Informatics, Machine Learning
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required) Experience with machine learning / deep learning (PyTorch; model training; GPU workflows). Experience with Transformers / text embeddings / multimodal modeling (e.g., Hugging Face ecosystem
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deep learning. You will contribute to several high-impact projects addressing hydrological extremes and their feedbacks within climate and human systems. Your work will have real-world impact, providing
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the fibre laser and deep learning domains. About you You will have a PhD in an experimental discipline or equivalent experience, ideally with experience in fibre optics and low-noise lasers and optical