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to work in an international collaborative environment. To thrive as a PhD candidate, it is crucial to have a strong research mindset driven by curiosity and passion for your topic. Reflecting on your
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PhD Position Simulating the Airspace of the Future: Fleet & Network Optimization for Future Aircraft
experience in building simulation environments. Experience with fleet planning, airline network schedulling, and/or optimization methods. Genuine interest in sustainable aviation. The candidate is proactive
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work together in an open and international scientific environment. Together they perform theoretical and experimental research in particle and astroparticle physics. KM3NeT is a next-generation neutrino
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using data from The Maastricht Study, you will help clarify their relevance in the etiology of disease. Your colleagues: You will be embedded in a collaborative research environment at Maastricht
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communications, wireless sensing, and non-terrestrial networks (NTN), addressing fundamental challenges in reliable, resilient, and sustainable connectivity. You will join an international research environment
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, and rewarding work environment, designed to help you grow both professionally and personally. For more information about the working conditions, please visit: https://www.universiteitleiden.nl/en
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, environment, society, and human adaptation behaviour You assess how adaptation can reduce climate risks under different climate scenarios You present your research at scientific conferences and publish your
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, biodiversity conservation and restoration, and the delivery of ecosystem services. It is a stimulating environment that combines first-class expertise with youthful enthusiasm. Curious about the team you would
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PhD Candidate: Modulating plant-based nutrition to enhance the sensory aspects and nutritional value
regional study participants in a clinical setting. What we offer At Maastricht University, you’ll work in an international, open, and engaged environment. We offer: A 12-month contract (1.0 FTE) with
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, matrix composition, and (anisotropic) matrix architecture are influenced by the mechanical and geometric properties of their environment. These computational models can provide crucial mechanistic insights