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uncertainty quantification. Addressing these shortcomings is a research challenge in both core machine learning methodology and the application domain. This project will tackle both in close collaboration with
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dynamics. Particular emphasis is placed on opinion dynamics as well as distributed problems in coordination, optimization, and learning. The research encompasses both theoretical and computational aspects
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
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distributed wireless systems" which is conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in
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application! We are looking for a PhD student for sustainable and resource-efficient machine learning. Your work assignments Machine learning has recently advanced through scaling model sizes, training budgets
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learning). The project will be carried out in a collaboration between Linköping University (main supervisor: Anders Eklund) and Lund University (co-supervisor: Mikael Nilsson) through an ELLIIT collaborative
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look forward to receiving your application! We are looking for a PhD student for sustainable and resource-efficient machine learning. Your work assignments Machine learning has recently advanced through
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learning with interactive exhibits in public spaces. The PhD student will collaborate closely with visualization researchers, AI-specialists, research engineers, educational scientists, and pedagogues
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application! We are looking for a PhD student in Statistics and Machine Learning Your work assignments We are looking for a PhD candidate to work in the intersection of computational statistics and machine
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position is on the machine learning method development. We will strive for a tight collaboration between the groups, including regular meetings and research visits. As a PhD student in the project, you are