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implement Python scripts for the automated control of electron microscopes; design and execute automated experiments, including real-time feedback loops between acquisition and data analysis; maintain
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surrogates of electronic Hamiltonians. The postdoctoral researcher will develop graph neural networks based on the MACE architecture to predict Hamiltonian elements for 2D materials and van der Waals
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: Conducting synthesis experiments of PtAg nanoparticles through galvanic replacement and related wet-chemistry routes. Performing image analysis of transmission electron microscopy (TEM) data to quantify
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chemical and structural manipulation, nanostructuring and interfacing materials that are identified as strategic in the roadmap for new technologies (hybrid metal-organic heterostructures, graphene-based
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this towards photonic and optoelectronic applications. In this project, you will work on optothermal effects in 2D materials. Main Tasks and responsibilities: To perform optothermal measurements, analysis and
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for the analysis of physicochemical, morphological and/or thermal properties after LNs fabrication will be performed. The Postdoctoral Researcher will also be using routinely in vitro techniques that can be applied
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responsibilities: Operate and optimize advanced STEM and FIB instrumentation for the nanoscale analysis of catalytic and energy-related nanomaterials, supporting the development of high-performance materials
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optimize advanced STEM and FIB instrumentation for the nanoscale analysis of catalytic and energy-related nanomaterials, supporting the development of high-performance materials for green hydrogen production
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, Computer Science, or related disciplines. Knowledge and Professional Experience: · Knowledge of programming languages used in data analysis (particularly python) is strongly recommended. · High Performance