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the development of a novel torsion test method to measure how oxidation and creep may interact at high temperatures or long times, thereby aiding the safe design, operation and lifing of plant designed for long
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application! We are now looking for a PhD student in Computer Vision and Learning Systems at the Department of Electrical Engineering (ISY). Your work assignments Your task will be to analyse and adapt vision
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. Desirable Criteria Experience implementing machine learning or deep learning models (e.g., neural networks, probabilistic learning methods). Knowledge of state estimation techniques, such as Kalman filters
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the home fees and international fees. Overview Interested in bioinformatics, and high-resolution mapping of human heart? This PhD project will investigate how computational geography methods can be scaled
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of numerical methods Geophysical fieldwork experience, preferably with GPR and EMI Strong English writing skills (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ), ideally
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metrics directly into the design loop to drive durable, resource-efficient components, validated against analytical benchmarks or experimental data. Where to apply Website https://www.jobbnorge.no/en
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if you have any of the following: Prior experience with inverse modeling or parameter estimation. Experience in microscopy or microfluidic lab environments. Experience with open-source codes
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Predicting infiltrative glioblastoma progression using advanced magnetic resonance imaging methods Project Supervisors: Michael Chappell, Steffi Thust Project Overview Glioblastoma (GBM) is the most
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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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bespoke methods – including advanced data modelling approaches (e.g., machine learning, digital twin models) and AI techniques where appropriate – to provide novel solutions that enable sports to make