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This multidisciplinary position is part of a WASP NEST (Novelty, Excellence, Synergy, Teams) project focused on advancing generative models and perceptual understanding in computer vision. The
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generative surrogate models for molecular dynamics (MD). MD is a foundational technology across the sciences and engineering, with translational applications in areas such as drug discovery and materials
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tomorrow. About the department The main competences at the Department of Industrial and Materials Science are found in the areas of: Human-Technology Interaction Form and Function Modeling and Simulation
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thermal conductivity b) Development of hBN thermal interface material that combines a high degree of compressibility and recovery c) Modeling, simulation and characterization of phonon transfer across
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, computational materials science, computer science, or a related field, awarded no more than three years prior to the application deadline*. Background in physics-based battery modelling and/or machine learning is
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efforts. The theoretical activities at Chemical Physics focus on electronic structure calculations within the density functional theory together with mean-field kinetic modeling and kinetic Monte-Carlo