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reclamation pilot-scale and lab-scale systems. Conduct membrane and separation process modelling, module-scale desalination system modelling, including conventional modelling and machine learning-based
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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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execution and milestone completion. Job Requirements Strong background in AI/NLP or speech technologies, with experience in designing and implementing machine learning models. Proficient in software
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, or behavioral data) and be proficient in Python and modern deep-learning frameworks (ideally PyTorch). Experience in computer vision, multimodal data fusion, self-supervised or generative modeling is highly
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. Demonstrated high level of achievement in related research productivity and academic writing. Technical skills in computer programming, algorithm development and deep learning model implementation, and practical
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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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reference. The student will focus primarily on the photonic integration of machine learning methods, contributing equally to the development of ML algorithms in this context. Their work will include
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Columbia (UBC) Vancouver campus invites applications for a full-time Postdoctoral Research Fellow with expertise in artificial intelligence (AI), machine learning (ML), and data science. The position will be
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, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
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clinical approaches, including: Histopathology and digital pathology (whole-slide imaging, WSI) Quantitative analysis of the tumour immune microenvironment AI-based image analysis, machine learning and deep