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the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
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has gone through a very rapid development in the last few years. Large-scale machine learning models are however notoriously over-confident. With insufficient amounts of data to train them on together
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. The research in the PhD project will focus on core spatio-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation
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-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation methods for data assimilation; and graph-based multi
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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, and the mathematical and computational foundations of neural networks. Familiarity with the following areas is meritorious: machine learning, computational complexity, tree automata and tree
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be in advanced courses in computer science, mathematics, AI, machine learning or similar. Alternatively, you have gained essentially corresponding knowledge in another way. The applicant is expected
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that you will help us to build the sustainable companies and societies of the future. The Machine Learning Group at Luleå University of Technology seeks a doctoral student in machine learning. We offer well
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both experimental development and theoretical modelling. Therefore, it requires the candidate to have a solid background in physics, electronics, and mathematics, along with strong practical experimental