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Field
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PhD Position Simulating the Airspace of the Future: Fleet & Network Optimization for Future Aircraft
current and future aircraft models + Evaluating how these differences affect fleet assignment and network planning + Optimizing airline operations (e.g., fleet composition, scheduling, routing) based on new
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PhD Position Simulating the Airspace of the Future: Fleet & Network Optimization for Future Aircraft
: Model development: + Characterizing the key performance differences between current and future aircraft models + Evaluating how these differences affect fleet assignment and network planning + Optimizing
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systems, optimizing audio playback levels, and supporting other acoustic interventions to improve occupant comfort and building performance. The research will adopt a human-centered approach, placing
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of biotechnology relevant compounds. Individual pathway enzymes will be characterized and optimized and fungal strains will be developed that result in optimal production while downstream processing aspects will
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replication, pathogenesis, and host-fungi interactions to inform rational drug design and optimization of antifungal therapeutics. Collaboration and Project Management: Coordinate with multidisciplinary teams
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glycobiology, radiopharmaceutical sciences, targeted radionuclide therapy, and translational research. Job description As a PhD student, you will: Develop and optimize radiolabeling strategies for glycosylated
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research projects. Questions about this position can be directed to [email protected] . Skills / Knowledge / Abilities The successful candidate will: · Design, develop, and lead independent and collaborative
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research projects. Questions about this position can be directed to [email protected] . Skills / Knowledge / Abilities The successful candidate will: · Design, develop, and lead independent and
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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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welfare services face several challenges related to decision-making processes, systematic practice, the use of research-based knowledge, and technological support. The digitalization initiative