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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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contribute to project reporting. Work with the interdisciplinary team of the group (theory, computation, machine learning) and support junior researchers on SOT-related topics. Requirements: Education: PhD in
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Research Engineer - Tools developer for LSQUANT platform (Theoretical and Computational Nanoscience)
Personal Competences: Demonstrated competitive ability in using DFT simulations, and machine learning techniques and DFT. Demonstrated strong coding skills and a passion for UX/UI design. Summary
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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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parameters affect material properties and functional performance, and interacting with machine-learning and modelling teams to translate experimental results into predictive datasets. Preparing reproducible
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: MSc in Physics, Materials Science, Nanoscience, Computer Engineering, Data Science, Gaming Engineering or a related discipline. · Knowledge: Strong coding skills in Python and knowledge in materials