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Field
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of machine learning / AI methods and their applications to experimental data; Knowledge of data science (statistics and quality control) as it relates to experimental data and ability to automate data storage
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of the following criteria: Technical competencies Knowledge of machine learning / AI methods and their applications to experimental data; Knowledge of data science (statistics and quality control) as it relates
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UiO/Anders Lien 4th October 2026 Languages English English English 3-years PhD position in probabilistic machine learning and statistics Apply for this job See advertisement About the position We
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in order to steer the emergent behavior of a collective. The base of the PhD project will be numerical simulations of active systems, where machine learning will be used as a tool to better understand
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PhD student (f/m/d) who wants to take ownership of the software ecosystem behind our computational imaging research – from experimental reconstruction algorithms used inside our lab to robust tools used
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and laser-scan data. These models underpin decisions impacting net-zero ambitions, yet interpretation remains slow and subjective. We need tools that make geological reasoning faster, more transparent
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-leading research in several fields. Notably, the groundbreaking discovery of the CRISPR-Cas9 gene-editing tool, which was awarded the Nobel Prize in Chemistry, was made here. At Umeå University, everything
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Assist in developing AI-based computational tools for analyzing biological images. Help implement machine learning, deep learning, computer vision, and image processing algorithms. Work closely with
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influencing factors and improve the accuracy, robustness and energy efficiency of intelligent sensing systems. Apply AI as an engineering tool: Use signal processing, statistical methods and machine learning
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research problem in its own right, advancing both the conceptual foundations and computational tools for assessing NLP systems in ways that are reliable, valid, and human-centred. Application domains include