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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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, Bayesian inference, model calibration, and Markov Chain Monte Carlo methods, uncertainty quantification, statistical modelling, and Gaussian processes, machine learning for time series, sequence-to-sequence
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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
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opportunities and diversity as a strength and an asset. Description of the workplace The research group for associative learning conducts research in neurophysiology and neuroscience, with a particular focus on
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2026, or as otherwise agreed. Description of the Doctoral Project and Research Group The doctoral position is based in the Pancreatology Research Group within the Division of Surgery at Lund University
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in the advancement of wearables, the Internet of Things, Industry 4.0, etc. The focus of this project is to apply this technology to machine components to give information about the operation. This
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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Subject area: Biology Description of the PhD projects We are seeking two PhD students in the field of biogas production, with a focus on the digestion process. The biogas process is currently
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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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. 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