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perform both empirical and theoretical work. You will learn how to collect and analyse data within your research area as well as communicate your results at national and international conferences and in
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systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
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and theoretical work. You will learn how to collect and analyse data within your research area as well as communicate your results at national and international conferences and in scientific journals
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for latent variables and their connections to modern machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates
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complex contexts through statistical models, machine learning (ML) methods, and artificial intelligence (AI). This includes working with performance, scalability, resilience regarding platform architectures
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with nuclear fuel modelling, machine learning
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high-resolution mass spectrometry, in vitro pharmacological characterisation of new psychoactive substances, as well as metabolomics and machine learning. As a PhD student, you devote most of your time
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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, micro-CT, particle size analysis, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is also beneficial. For further information about a
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, statistical methods, or machine learning is considered a merit. Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University´s rules and guidelines