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Materials and Devices (AEMD) group focuses on the material sciences and technology aspects of novel electronic materials, with a strong emphasis on graphene as well as other 2D materials (MoS2). The group
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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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. 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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widely used by the academic community (about one thousand citations per year), and has been a flagship code of the MaX European Centre of Excellence for exascale computing in Materials Science (www.max
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PhD position funded by AEI agency (Spanish Government) TOPIC: Magneto-ionics for information technologies: secure and energy-efficient memories and advanced computing A PhD position is available
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and cleanroom infrastructure. The candidate must possess the technical expertise to ensure the smooth daily operation of equipment, troubleshoot issues, and implement an effective maintenance program to
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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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or MSc (or near-completion) in Physics, Materials Science, Computer Science, Electrical/Computational Engineering, or related field. - Hands-on Python (data wrangling, scripting, automation); comfort with
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). Keep experiments reproducible (scripts, configs, logs) and write a short technical report. Requirements: Minimum required: - Enrolled BSc (Year 3-4) in Physics, Materials Science, Computer Science
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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