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(Kubo / linear-response and non-equilibrium Green function formalisms) and implement them numerically in the group codes, on tight-binding and DFT-derived (Wannier) Hamiltonians. Validate the extended
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guided by theoretical predictions and will combine magnetotransport measurements with material growth and characterization, including MBE and angle-resolved photoemission spectroscopy (ARPES). What We
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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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for energy materials or catalysis, skills on in-situ TEM and AI ML/DL coding skills will be a plus. Experience collaborating in international, multidisciplinary projects is a plus. Hands-on experience working