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, increasing energy absorption - an essential feature for aerospace applications. This project aims to deepen the understanding of how alloy composition influences properties and processability in solute-lean
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other national, international longitudinal studies, and administrative data sets, to examine the mechanisms and processes of key social and emotional core competencies that can be cultivated in schools
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processing (e.g., baking), and identifying transformation and degradation products using high-resolution mass spectrometry (HRMS) and advanced data-processing tools. This project offers a unique opportunity to
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emissions, and enhance occupant health and wellbeing. As a Research Assistant, you will work closely with UK- and Egypt-based teams to analyse collected data, develop and test computer-based retrofit models
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responses and recovery in humans. To this end we combine data from psychopharmacological experiments in healthy participants and real-world clinical data from surgery patients for a more in-depth
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learning in simulated and indoor/outdoor environment. Reasonable results can be achieved in high signal-to-noise ratio environments; further research is required to improve deep learning in fast variation
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to scale up and demonstrate sustainable processes for industrial (bio)manufacturing of pharmaceuticals by integrating environmentally friendly technologies and processes. However, given the complexity
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the understanding and chemical characterization of advanced bio-oils derived from lignocellulosic biomass and municipal solid waste. This research is critical for the commercialization of bio-oil upgrading processes
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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 from YouTube. Accept
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the appointment is based on a previous qualifying position PhD Fellow, research assistant, or the like in such a way that the total time used for research training amounts to three years. We process personal data