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-scale simulation, signal and image processing, time-series analysis, optimization and control, computational inverse problems, and artificial intelligence methodologies. The field of teaching is
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to understand the damage and repair processes in the central nervous system (CNS) with the aim to unlock the endogenous repair potential. The group has a strong focus on neural regeneration and disease
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researcher will develop image processing methods to analyze soil structure more deeply than conventional methods. The work also includes using image-based numerical flow simulations to determine soil hydraulic
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) in a relevant field, e.g. cell biology, biomedicine, biochemistry, molecular biology or biomedical imaging. The candidate should be highly motivated and committed to obtain a PhD degree, show genuine
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according to the guidelines, i.e., a written description of pedagogical training and teaching merits (Instructions on the JYU Work with us website) . Degree certificate (highest degree, a PDF copy/picture
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functions is therefore crucial in the process of model development to the specific tasks at hand. For instance, the Hyvärinen score matching principle has been widely applied in AI systems, particularly
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settings. Using advanced compressed sensing techniques and machine learning methods, PulseZTE will make it possible to image neural activations and vascular pulsations simultaneously. It will also enable
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intelligence. The project also aims to expand this modelling framework for spatially continuous forecasting by combining information from satellite images and species communities. Methodological research is
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they employ. The design of loss functions is therefore crucial in the process of model development to the specific tasks at hand. For instance, the Hyvärinen score matching principle has been widely applied in
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handling, behavioral studies, MRI laboratory work, fMRI experiments, signal processing and image analysis methods. The aim is also to transfer the new MRI methods to clinical scanners and thus there is a