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Vacancies PHD POSITION ON MULTILAYER GROWTH OPTIMIZATION BY HYBRID X-RAY METROLOGY (MOXY Key takeaways Nanometer-thin films are enabling factors in many advanced technology fields such as
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life-long follow-up. In the ZonMW-funded AI for EVAR project, we develop multi-modal models for optimized selection of treatment before, and follow-up after EVAR. You will implement and advance
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developing morphing surfaces enabled by Shape Memory Alloys (SMAs). These adaptive winglets are designed to optimize aerodynamic performance by responding to temperature variations and incorporating active
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. The use of such fibers requires new compounding strategies to optimize compound performance. In the proposed study, both dipped and undipped short-cut fibers will be incorporated into tire compounds
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structures. Other aspects of the research include a numerical framework for the sensitivity analysis to facilitate design optimization and experimental system identification. Information and application
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contributes to improving large-scale plasma simulations that are essential for the design and optimization of nuclear fusion devices, a key step toward future sustainable energy technologies. You will conduct
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, which relies on Dynamic Mechanical Analysis (DMA), requires tread compounds to be heavily optimized for snow performance to ensure compliance with regulatory snow tests. However, this often leads
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generative design approach needs to be developed to rapidly design globally optimal (e.g., cost, feasibility, contribution to energy efficiency, resource availability, and potential for mass execution
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subgroups with rapid disease progression or poor treatment response. This will enable more personalized treatment ultimately improving the health of thousands! Job description In addition to optimizing
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for mastering magnetron sputtering of piezoelectric thin films. This includes: Exploiting new deposition schemes and parameters of reactive magnetron sputtering, aiming for optimal piezoelectric thin film