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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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large upfront costs, but with ongoing cost savings once investments have been made. The liability to make these investments is tied to ownership of expensive assets (residential property). Other issues
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if the necessary clean energy and energy infrastructure is available at competitive costs. Large-scale investments in the energy sector meanwhile get off the ground only if industry is prepared to electrify its
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. This creates a large loss of value of strategically valuable raw materials and waste of energy related to material, cutting tools and parts production. The PhD project will therefore focus on automating and
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. Background and aims: As we move towards the future of large communication networks and remote sensing, applications such as 6G communications will require higher data rates, wider bandwidth, and stronger
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proficiency in R or Python for data analysis and modeling. Familiarity with analyzing large-scale healthcare datasets and real-world data. Experience in developing and applying simulation models, including
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analyse your data You will be coordinating the collaboration with CCIT, which involves retrieving samples and clinical data from a team of doctors. You will have to present in lab and section meetings
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attachment. Main tasks Collect, compile, and analyze data to map the responses of plants and pollinators to climate change Participate in the development and adaptation of statistical models for analyzing
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. At NTNU, 9,000 employees and 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. ... (Video unable to load
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using state-of-the-art measurement systems such as LC-(HR)MS? This might be the next step for you! Pyrrolizidine alkaloids (PAs) are a large and structurally diverse class of plant-derived toxins, with