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Engineering, Data Science. Knowledge: Deep expertise in electron microscopy, particularly STEM and EELS methods. Proven experience in designing and conducting in-situ TEM experiments. Familiarity with energy
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, engineering or physics. Knowledge: Computational programming, machine learning, quantum transprot, device simulation. Professional Experience: use of device simulation codes applied to 2D materials. Personal
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approaches, where data storage and processing occur simultaneously at the materials level, inspired by the operation of the brain. This includes research on unconventional computing paradigms, such as
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areas of nanoscience and nanotechnology. Job title: Postdoctoral Researcher in Altermagnetic Spintronics Research area or group: Physics and Engineering of Nanodevices Description of Group/Project
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with programmable polarization for analog memory and spike-based computing. The researcher will work in a multidisciplinary environment combining thin-film growth, AFM/KPFM, electrical characterization
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programme. Requirements: Education: PhD in chemistry, chemical engineering, materials science, biochemistry or equivalent. Knowledge: Extensive expert use of an array of physicochemical and materials
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Physics, Materials Science or an equivalent field, with a background in condensed matter theory or computational nanoscience. Junior postdoctoral profile (R2). Knowledge: Spin-orbit torques and spintronics
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call ICN2-SO Technology Valorisation Programme, supported by the Severo Ochoa Grant CEX2021-001214-S/MICIU/AEI/10.13039/501100011033 The selected candidate will contribute to the technical execution
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international recognition from scientific societies or science academies. Cobine strong expertise in theoretical and/or computational methods with proven leadership and management skills. The ability to mentor
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evaluation and development of novel PEC systems. · Design and implement in-situ TEM experiments using the available gas and liquid sample holders to study dynamic processes in real-time, under controlled