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microscopy (QPlus AFM), integrated with electron spin resonance (ESR) capabilities. Your profile We are looking for a highly motivated experimentalist who meets the following criteria: PhD in Physics
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selection process with applications accepted year-round. Eligibility requirements: Candidates should hold a PhD degree in computer science, data science, mathematics, physics, statistics, or electrical
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other exciting projects ranging from autonomous sputter deposition to the development of new ferroelectric materials for non-volatile memory applications. Your profile PhD degree in physics, materials
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PhD in Computational Materials Physics or a related area is required. Experience with electronic structure calculations is essential. Familiarity with the use of machine-learning tools in materials
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(e.g., deep learning, explainable and physics-informed AI, large language models, etc.). The position will be developed within the funded project entitled “UrbanTwin: An urban digital twin for climate
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one of the programmes. It is home to a community of over 100 PhD, postdoctoral and Professorial researchers working on diverse themes related to sustainable cities and resilient infrastructure systems
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qualifications with a PhD in physics, electrical engineering, materials science or a related subject, and a background in magnetic thin films, nanostructures and spintronics. You should be motivated, proactive and