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Field
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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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requirements PhD in Physics, Applied Mathematics, Computational Science, or a related field Strong background in machine learning, particularly in the development and application of neural networks
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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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UiO/Anders Lien 8th March 2026 Languages English English English PhD Research Fellow in Machine Learning and Statistics Apply for this job See advertisement About the position Integreat
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or working with complex datasets, ideally from experimental or sensor-based systems. Hands-on experience with machine learning, including deep learning, probabilistic models, or physics-informed approaches
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Informatics, Health Data Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated
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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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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
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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed
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candidates/candidates who are in the closing stages of their master’s degree can also apply Solid background in artificial intelligence and machine learning, including deep neural networks Programming