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interface between ESM and the latest version of SIESTA, its validation, its benchmarking, and its exploitation in scientific applications. Work will also involve the optimization of SIESTA on the fastest and
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, construction, and operation of optimized stellarators and other superconducting fusion devices. Candidates at all career stages, from Assistant Professor to Chair Professor and from junior to senior Researchers
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ESEM, a FIB system, and a complete suite of sample preparation tools. The role will involve the coordination of day-to-day operations of the unit, ensuring optimal equipment performance, user
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, with a highly innovative research and technology transfer project, this could be your opportunity. Main Tasks and responsibilities: To develop and optimize the analytical performances of the multipled
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this short-term project we will use active learning to accelerate the training of deep learning algorithm to optimize 2D material Van der Waals structure discovery. Main Tasks and responsibilities: The person
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Instituto de Investigación Sanitaria Puerta de Hierro – Segovia de Arana (IDIPHISA) | Spain | 15 days ago
Integration with reference architectures and data space components - A4.1 Development and optimization of federated models - A4.2 Integrated testing and model validation - A5.1 Communication
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multidisciplinary environment. PhD Research Focus The selected PhD student will contribute to the design, fabrication, and optimization of electrochemical devices, exploring novel electrode materials, miniaturization
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and responsibilities: Testing of the microscope's components to assure full functionality. Installation of the system. Adapting the control electronics and software for optimizing user-friendly
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defect engineering in cerium oxide nanoparticles to optimize their redox activity and catalytic properties. This involves aqueous, room-temperature synthesis methods, advanced spectroscopic
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methods to accelerate the discovery and optimization of novel materials, and actively develop large-scale materials models (AI for Science) to transform the R&D process through AI-driven paradigms. In