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vacuum conditions. Your tasks include: • Design and manufacturing of propulsion prototypes • Experimental testing and diagnostics • Modelling and performance analysis • Development of propellant-control
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deploying the face de‑identification pipeline on resource‑constrained hardware, optimizing the underlying AI models based on latency, memory, and power constraints, and building demonstrators that showcase
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to contribute to high-tech applications, state-of-the-art modelling or experimentation of advanced sustainable materials across the scales? We are looking for outstanding and enthusiastic PhD candidates, with a
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to develop engineering interventions to improve plant regeneration, seed longevity and defenses against disease. Your task will be to further develop two-dimensional and three-dimensional models of plant
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multi-fidelity modelling, your research will advance and integrate three core elements: (i) physics-based multi-fidelity structural models enabling high-resolution analysis at fatigue-prone hot-spots
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algorithms. model and optimize end-to-end physical-layer performance, hardware non-idealities, and overall power consumption. focus primarily on space and security topics (satellite communications, reliable
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agricultural sector in which agriculture goes hand in hand with soil health and nature restoration, and a good revenue model for farmers. Between now and 2030, ReGeNL will start the transition to regenerative
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of both the basics and the latest developments of machine learning, in particular large language models and other generative AI modelsOperational Language Requirements: Fluent written and verbal
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building models (impervious and with openings) capturing loads and pressures on various structural elements, both horizontally and vertically. Integrating experiments with numerical simulations (e.g. CFD
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theory and non-standard logics, preferably within one of the two branches of the project: Modal Logic of Forcing Inner Models from Extended Logics These are active fields within set theory, with many