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highly motivated PhD student to develop advanced models for predicting the fatigue life of additively manufactured steel in nuclear reactor water environments. The project focuses on modeling corrosion
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geometries and process-induced defects demand new inspection approaches. The project combines modelling, sensor fabrication, experiment, and data analysis. You will work with a team of experts to develop
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for predictive modeling scenarios, causal modeling is also within the scope of the position. The position is embedded in the ten-year gravitation grant Stress in Action, funded through NWO (Dutch National Science
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profiling of patient samples is essential to predict responses, identify candidate biomarkers and personalise therapy aimed at harnessing the immune system to target the tumour. This is a challenging
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sources of quantum light for optical quantum computers. The project takes place in the Quantum Light Sources group at DTU Electro, where we design, model, fabricate and test sources of single photons
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operating model and governance structure that ensures reliable service delivery, strong change control, appropriate separation of duties, and alignment with institutional priorities. In addition, the Director
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outcomes, and multi-OMICS profiles, the project will generate predictive models to guide safer and more effective, individualized steroid use. As such, the candidate will be responsible for data
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, better adapted individuals can be selected at the seedling stage using only genetic data, accelerating the breeding cycle. Incorporating information about plasticity can aid genomic prediction modeling
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modeling, machine learning, or data-driven prediction methods applied to environmental datasets. Experience building and maintaining large, frequently updated archives of weather or climate observations
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the complex multiscale nonlinear interactions at the origin of such extreme events. In this project, you will develop machine learning-based reduced-order models which can accurately forecast