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Field
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within LTU’s AIC³ Lab (Automation, Industrial Computing, Communication, and Control Laboratory). Subject description The research subject focuses on an integrated development of network architectures
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backgrounds, detector performance, and physics sensitivities. One concrete example is the use of different codes for simulating critical backgrounds, comparing their predictions and developing methods for how
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provides a unique opportunity to work at the intersection of AI and experimental science, combining fundamental algorithmic development with real-world applications in scientific imaging. Due to limitations
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(especially silicon-based) and cathode applications. In this role, you will: Develop new binder systems for electrode processing. Synthesize and modify binders for innovative manufacturing processes. Balance
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can reduce model accuracy, especially when modeling multiple processes that interact across different spatial scales. To address this, the project will develop a new class of raster data-processing
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control and reinforcement learning supported by an edge-cloud-based wireless communication environment. The doctoral student will work on data-driven theory and method development in simulation environments
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at the Faculty of Engineering and contribute to cutting-edge research in radar systems. The radar group at BTH has extensive experience in radar research, developing signal processing algorithms for long-range
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growth. The 60 doctoral students within the department are a diverse group from different nationalities, backgrounds and fields. We offer very good employment conditions, and administrative and technical
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equality, where different experiences generate conversations between people and pave the way for science, creativity and development. Therefore, we welcome applications from people with diverse backgrounds
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a long-term difference in society. Our most important assets are all the individuals whose curiosity and dedication make Uppsala University one of Sweden’s most exciting workplaces. Uppsala University