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Field
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In this project, the selected candidate will join us in conducting research in statistical learning, developing data-driven methods to learn models of large-scale signals and systems from data
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at the tumour margin represent a key target for earlier and more effective therapeutic intervention. This PhD project will develop advanced MRI analysis methods and imaging-driven predictive models focusing
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mangament in numerical models, including advanced calibration strategies from data (observations, measurements, other model predictions) and uncertainty reduction. Scientific context Many engineering and
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mechanism. The integrating should enable to guarantee certain properties of the learned functions, while keep leveraging the strength of the data-driven modelling. Most of, if not all, the traditional
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cartilage tissue engineering? Are you driven to develop novel in silico frameworks that deepen mechanistic understanding of tissue growth and inform in vitro experiments? Then you might be our next PhD
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systems. By combining microclimate modelling, remote sensing data, and data-driven methods, the results are integrated into a Digital Twin framework. The research will support predictive risk assessment and
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will focus on understanding, modelling, and controlling these topologically-protected spin waves, addressing both fundamental questions and potential applications. Your job This project consists of a
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3 Apr 2026 Job Information Organisation/Company Utrecht University Research Field Computer science » Cybernetics Computer science » Programming Engineering » Computer engineering Engineering
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12 Apr 2026 Job Information Organisation/Company Umeå universitet Department Umeå University, Faculty of Science and Technology Research Field Physics Researcher Profile First Stage Researcher (R1
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harmonisation, and next generation research infrastructures. You will contribute to research projects enabling secure, interoperable, and scalable AI-driven use of clinical data for complex diseases such as