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Alexander Neimark (Rutgers University), Dr Mathias Steiner (IBM Research), and Dr Yongqiang Cheng (Oak Ridge National Laboratory). Together, the team integrates molecular and ab initio simulations, machine
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] * Background of the recruitment and description of the project Our team studies the nontrivial electronic properties of strongly correlated and topological materials using ab initio approaches. We aim to predict
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machine-learning and high-throughput methods, to ab initio calculation of electrochemical reaction kinetics. The position is funded by the Swedish Energy Agency’s research program “Sustainable Battery Value
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-to-olefins, syngas-to-olefins) involve the production of hydrocarbons from renewable raw materials. In addition to periodic density functional theory (DFT), ab initio methods and molecular dynamics (MD
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computational methodologies, ranging from atomistic and electronic-structure–based materials modeling and characterization, via machine-learning and high-throughput methods, to ab initio calculation
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ultrasonic and/or laser acoustic measurements - Material characterization using electron microscopy techniques - Ab initio calculations of phase diagrams and material properties - Thermodynamic modeling - Data
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general, and specifically on systems with characteristic nanoscale features. They use finite element and ab initio software as numerical tools for modelling and analysis. We are seeking highly qualified and
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: Machine Learning Molecular Dynamics. The project involves the development and application of machine learning methods that enable a major boost of the time and length scales accessible to ab-initio/first
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Description: Apply Position Description We invite talented and motivated applicants for PhD and Postdoc positions in the group of Haowei Xu (https://www.haoweixu.com/ ) at the Department of Physics, City
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”. In: J. Chem. Phys. 158.3 (2023). [5] : Kästner, J. “Umbrella sampling”. Comp. Mol. Sc., (2011), 1(6), p. 932-942. Techniques/methods in use: Molecular dynamics, Ab-Initio Molecular Dynamics