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internal reports and manuscripts. Requirements: PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related. Solid knowledge of machine learning, including graph neural
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: · Education: PhD in Materials Science or similar. Knowledge in tech transfer will be highly valuable. · Knowledge: Advanced materials development Polymeric materials development, functionalization
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: · Education: PhD in Materials Science or similar. Knowledge in tech transfer will be highly valuable. · Knowledge: Advanced materials development Polymeric materials development, functionalization
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areas of nanoscience and nanotechnology. Job Title: Postdoctoral researcher Research area or group: Nanostructured Materials for Photovoltaic Energy Project title: Synthesis and Engineering of Pb-free
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to) SIESTA (www.siesta-project.org) and its TranSIESTA functionality. SIESTA is a multi-purpose first-principles method and program, based on Density Functional Theory, which can be used to describe the atomic
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applications. The candidate will help on MSc and PhD students supervision and training. AVAILABLE INSTRUMENTS Thermo Fisher Spectra 300 (60-300 keV), double corrected and monochromated, Gatan Continuum EELS with