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many limitations (e.g., from a cognitive point of view) and they cannot fulfill alone the wide range of tasks that humans can do. Thus, this PhD will propose novel planning and control methodologies
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Neural Networks (SSM-SNNs). The project includes the co-design and integration of a RISC-V processor for hybrid neuromorphic computing. The research aims to develop ultra-low-power computing chips
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strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives
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motivated candidate with a background in chemical or process engineering and strong experimental and analytical skills. Join us to drive innovation in carbon capture and contribute to shaping Europe’s low
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complement to wind and solar power in climate-neutral power systems. They can deliver a range of services, ranging from arbitrage (charging the system during low-price periods and discharging during high price
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of the biggest challenges is the development of efficient, scalable, and low-noise control electronics that operate at cryogenic temperatures. This PhD project addresses this challenge by designing CMOS-based
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the end of the project, the student will be able to estimate whether AM materials will be able to withstand these different environments better than or as well as components made by traditional materials
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43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position Are you excited about sustainable
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capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives, including large-scale
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) fertilizer use has caused environmental contamination in some regions, while P-deficient soils and limited fertilizer access constrain crop production in others. Climate change and dwindling high-grade