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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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research lines. Research line 1: "Digital twinning for 3D network optimization" focuses on developing distributed digital twin architectures and mechanisms for distributed network optimization in networks
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the difference between the International fee and the Home/RoI fee. There will be a package of support to enable you to develop a research career in this exciting field. The Royal Berkshire Hospital has 20 surgical
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 24 days ago
Mathematical Modelling of kinetic and thermodynamic performance of material to optimize the production process. The research has significant real world impact. It is expected to deliver a step change in
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Decision Intelligence for Supply Chain and Operations Optimization. The successful candidate will contribute to cutting-edge research at the intersection of Statistical Machine Learning and Generative
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with respect to high level research, training and innovation within manufacturing engineering, in an exciting combination of academic and industrial environments. The selected candidate will receive
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committed to research and innovation, aiming to establish itself as a world-class university in its areas of expertise. Located in Benguerir, at the heart of the Green City, UM6P actively contributes
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, scalability, and adaptability to various applications such as autonomous systems, IoT devices, and wearable technologies. Research Focus Areas: 1- Neuromorphic and AI-Optimized Processors: Design AI-specific
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industry’s biggest challenges: Closed-Loop Design and Optimization of Biologics. The research program will build on the recent advances in protein design, automation, and multi-parameter optimization and
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control