36 pattern-recognition "https:" "CMU Portugal Program FCT" positions at Linköping University
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application! Work assignments The division of Media and Information Technology is an international leader in visualization, with research, development and education in design, engineering and use of visual
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circuit design and collaborates closely with major semiconductor companies and academic research organizations worldwide. Feel free to read more about the division here: https://liu.se/en/organisation/liu
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in clinically relevant environments. Key work assignments include: Design, fabrication, and optimization of high-performance plasmonic nanostructures and SERS substrates for sensing in complex
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of Sweden and is part of the EU’s ambitious AI Factories initiative. Learn more: https://mimer-ai.eu/about-mimer/ , https://www.naiss.se , https://eurohpc-ju.europa.eu/ai-factories_en We are now looking for
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competitive advantage (https://liu.se/en/research/cbmi ). You will work under the supervision of Professors Christian Kowalkowski and Daniel Kindström. Research at IEI spans a broad range of areas, from
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decentralized machine learning in 6G networks, and design machine-learning algorithms that can handle the network imperfections that remain impractical to resolve at the physical layer. The focus of the research
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that promote metastasis. You will contribute to research that also encompasses other tumor types and their metastasis patterns, with the goal of developing new insights that can improve clinical practice and
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synthesis, material science, theory and modeling, device physics, nanotechnology, biotechnology, and system design. Our activities span the range from basic research to commercialization, the latter carried
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, design, and conduct research on integrated circuits taking on the challenges of next generation communication systems. The project aims to investigate the feasibility and advantages of new design
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especially crucial in applications such as medical diagnosis, weather forecasting, and aircraft design. To improve the reliability and trustworthiness of mathematical models and machine learning tools (e.g