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closely related discipline. You have a strong background and prior experience in atomistic and molecular simulation techniques, specifically density functional theory (DFT) and molecular dynamics (MD
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that can be benchmarked through physical experiments or computational simulations. The project is funded by the Research Council of Norway and is a collaboration between NTNU and Norsk Regnesentral
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for molecular magnetic materials lags behind these experimental breakthroughs. DFT fails to capture strong correlation, while wave function-based methods are computationally prohibitive for strongly-correlated
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highly challenging task. The project uses Machine Learning (ML), in combination with DFT and state-of-the-art Boltzmann transport methods, to predict, accelerate, and scale the computation of electronic
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Materials Science (CMAT) is looking for: Doctoral researcher (PhD student) in area-selective atomic layer deposition (AS-ALD) simulations Are you interested in discovering and understanding chemical