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in neuroimaging methods. You have experience with computational modelling and/or quantitative data analysis, preferably using tools such as Python, R, MATLAB or similar software. You have an affinity
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models. We further propose to develop scalable structure learning methods for these new models, including latent variable identification, and to demonstrate their effectiveness on real data. For this, we
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be computed using the appropriate modelling techniques. Method and models will be developed when necessary. Job requirements The ideal candidate: Holds an MSc in Mechanical, Chemical, Materials Eng
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-static beamforming methods, and semi-tomographic reconstruction algorithms that enable high-quality 3D visualization of the abdominal aorta. In addition, you will develop algorithms for segmentation
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complex environments. The project will build on an interdisciplinary approach, combining concepts and methods from physics, chemistry, and mathematical modelling. The long-term goal is to derive design
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generation in PBMAs; contributing to the development and optimization of analytical methods; publishing your results in peer-reviewed scientific journals and presenting them at (inter)national scientific
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no biorefinery) instead of fossil raw materials, green routes for polymer synthesis and processing, as well as chemical recycling/reprocessing methods (biodegradability, depolymerization, dynamic bonds) to make
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entails biobased building blocks (but no biorefinery) instead of fossil raw materials, green routes for polymer synthesis and processing, as well as chemical recycling/reprocessing methods (biodegradability
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related field. The availability to start your PhD on December 1, 2026. Hands-on experience with experimental methods (in water technology) for biological nitrogen removal and characterization. Proven
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stimulation (TUS), a novel noninvasive method for targeting deep brain structures University of Maryland, Maryland, United States Bas Ankoné (Rijksuniversiteit Groningen) A new political climate? Innovating