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machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
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machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
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south of Oslo. Main responsibilities The position is part of the SmartForest project (www.smartforest.no ), funded by the Research Council of Norway. The main task is to develop deep learning models
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areas of concerns to improve healthcare delivery to people with a learning disability and autistic people. We are contracted to deliver an annual report, regional reports and a number of deep dives as
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informed neural networks (PINN) and explainable machine learning (EML) frameworks; experience in related technologies including large-scale data analysis, deep learning, Python, PyTorch; and the ability
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for materials science, and advanced optimizers for modern deep learning. The research may be conducted in collaboration with the Electronic and Photonic Materials and/or the Computer Vision Laboratory
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implementation of deep learning and computer vision frameworks across a range of research projects. This includes developing and training deep learning models for tasks such as scene understanding, object
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aim to develop sustainable fishing techniques grounded in a deep understanding of flatfish escape behavior and swimming biomechanics. Your Duties and Responsibilities: Design, construction and testing
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learning. The employment is full-time for two years starting from August 1st 2025 or by agreement. Apply latest April 7th 2025. Project description Geometric deep learning refers to the study of machine
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at least one year of postdoctoral research, have experience with data visualisation, and be enthusiastic about engaging with different online communities to learn more about public uses of the past. They