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Job Description Do you want to be part of a section that aims to reduce the time required for and increase the value of physical testing of wind turbine structural components by using high
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i.e. turning towards in-line production and quality control will help save natural resources as well as reduce waste material and energy consumption. Formulation and test methods using mathematical
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develop the needed extensions for this project. Implement and test the new methodology of your PhD project Create ground-truth datasets for training, validation and test of the methodology Participate in
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of high-current power converters. Designing circuits, prototyping and testing in the lab. Any candidate who: has a good grasp of various power circuit topologies for DC-DC converters; is familiar with power
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to the development of machine learning frameworks You are eager to elaborate on the newest research results, improve ideas, and test/validate by engagement with national and international collaborators You will have
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, synthesis, characterization and test for sustainable energy solutions We also have research activities in our three interdisciplinary centers relating to nuclear energy, catalysis, and visualization
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of solvers for stochastic optimization problems, and test the methods on real-life data. As part of the PhD you will be following advanced courses to extend your skills, implement and test algorithms, and
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expression and developability. Propose and validate optimization tools for performing (Bayesian) design of experiments. System validation and iterative refinement based on empirical data. Test and refine
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to: Design and conduct research projects in collaboration with the supervisory team Examine and analyse data on startups supported by BII Collect and analyse additional quantitative and qualitative data from
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, laboratory testing and data augmentation. Your main goal will be to develop predictive models for assessing the degradability of bioplastics, facilitating a transition to more sustainable materials. More