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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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computing. With extensive experience in medical image analysis, computer vision, and AI systems through collaborations with leading institutions. Key Responsibilities: Conduct advanced research in the areas
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in image processing, quantitative analysis, and biological interpretation Proficiency in AI/machine learning tools for image segmentation, transformation, registration, or tracking Solid mathematical
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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or veterinary contexts. Strong foundation in computer vision and machine learning frameworks (e.g., PyTorch, TensorFlow, OpenCV); experience with video annotation tools and datasets. Hands-on experience with
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
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integration and AI models tailored for fish behaviour, health, and stress signal analysis. Investigate and apply novel machine learning and deep learning techniques for pattern recognition, classification, and