10 learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" PhD scholarships in Sweden
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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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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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Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking
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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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machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates will have the opportunity to collaborate closely
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modeling of protein dynamics We are seeking a highly motivated PhD student to join a DDLS-funded project at the interface of structural proteomics, protein biophysics, and machine learning. The position is
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malignancies. The doctoral training is carried out through participation in the various components of the projects, enabling the student to progressively acquire knowledge in scientific methodology, experimental
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about Umeå university as a workplace Description of work About the
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or heterogeneous environmental datasets Familiarity with spatial analysis, GIS, or geospatial data workflows. Experience with machine learning, modelling, or systems analysis approaches Interest in resilience
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and eager to acquire the relevant techniques over the course of the PhD. Solid working knowledge of cell wall integrity signalling in plants. Experience in RNA isolation from diverse organisms and