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Field
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for model selection, validation, and workflow design, while more broadly contributing to a deeper understanding of what it means to trust unsupervised learning as an exploratory tool in scientific machine
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an advantage if you have Interest in the mechanical behavior of materials. Experience with machine learning and/or programming/coding. Experience with finite element modeling from civil, mechanical, or marine
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analysis and learning models applied to brain and physiological signals. The objectives of this fellowship are: 1. Survey of the state of the art in science and technology of artificial intelligence models
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statement of motivation and a description of your experience with up to two of the topics: (a) AI, machine learning, and large language models for measurement challenges, (b) identifying and investigating
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North America, to improve an existing model for the spread of Cyvirus cyprinidallo3 (also known as Cyprinid Herpes Virus or CyHV-3) as a biocontrol agent for common carp in Australia. The modelling will
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North America, to improve an existing model for the spread of Cyvirus cyprinidallo3 (also known as Cyprinid Herpes Virus or CyHV-3) as a biocontrol agent for common carp in Australia. The modelling will
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UiO/Anders Lien 24th March 2026 Languages English English English Join the inclusive University of Oslo as a PhD Research Fellow in Machine Learning, tackling real-world data challenges! PhD
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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challenge issues, using advanced machine learning models and necessary techniques; (d) evaluate and validate the performance of proposed methods and algorithms through theoretical analysis; (e) maintain
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quantitative field), and will have applied experience in machine-learning, with extensive experience of hands-on model development, testing, validation and deployment using real-work datasets in operational