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Computational Chemistry, Materials Science, or a related field. Strong background in computational chemistry techniques, including molecular dynamics, quantum mechanical simulations, and machine learning
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dynamics, quantum mechanical simulations, and machine learning. Proficiency in programming languages and computational software’s. Strong motivation and passion for research in the field of sustainable
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behavior within the storage system to optimize design and performance. Demonstrated proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics (MD) simulations, enabling the computational
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proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics (MD) simulations, enabling the computational investigation of material properties, electronic structure, and atomic-scale behavior
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network of universities and research centers around the continent to link real field issues with up-to-date science. The institute consists of a multidisciplinary team of agronomists, biochemists, molecular
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operations and chemical processes. Ability to conduct experiments. Experience in using both steady-state and dynamic modeling, simulation and optimization tools, e.g. Aspen, Pro/II, GAMS, gProms... Ambitious
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advanced characterization methods of inorganic materials and their assemblies, ideally with a focus on battery materials. Demonstrated proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics
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assemblies, ideally with a focus on battery materials. Demonstrated proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics (MD) simulations, enabling the computational investigation
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CFD methods DFT and Molecular modelling linked to CCUS Strong analytical and problem-solving skills, with an ability to interpret and analyze simulation and/or experimental results. Ability to work in
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. Strong knowledge of heterogeneous catalysis and computational chemistry. Experience with computational modeling (i,e, DFT, and/or molecular dynamics). Familiarity with software such as Material Studio