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. Requirements: Minimum: PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related field. Demonstrated experience implementing heuristic/metaheuristic optimisation (e.g
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fields. Main tasks and responsibilities: · Operate and optimize advanced STEM and FIB instrumentation for the nanoscale analysis of catalytic and energy-related nanomaterials, supporting the development
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: Education: ·PhD in chemistry, biochemistry. Master in similar fields will be positivitely valorated. Knowledge and experience: ·Background in biosensor devices and clinical applications ·Knowledge in
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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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and 2D materials, and oxides. Fabrication of functionalized Pb-free MHPs by solution processing methods. Fabrication of complete Pb-free MHPs solar cells and memristors (TFTs). Stability analysis
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benchmarking. Contribution to SIESTA training events. Contribution to other activities in the group. Requirements: PhD in Physics, Materials Science, Chemistry, Computer Science, or related disciplines
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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
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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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papers. Requirements: Education: PhD in Physics or related degree Knowledge: Complex oxides (Ferroelectrics, antiferroelectric, nickelates, etc), nanomechanics, photovoltaics, scanning force microscopy