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have expertise and experience in executing density functional theory (DFT) calculations, microkinetic modeling, kinetic Monte Carlo simulations, and Machine learning methods. Minimum Qualifications: Must
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for the simulations with MD and DFT of zeolite catalytic processes, and will participate with the research group, to synchrotron coherent diffractive imaging experiments. This position is part of the funded FAPESP
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data. The topic will require numerical simulations and collaboration with colleagues working with DFT tools. Numerical 3D simulations of complex nano-devices using commercial or in-house software
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deposition (ALD). The project involves performing quantum mechanical calculations (e.g., first principles density functional theory (DFT)) to identify the structures and to understand the complex mechanisms
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are seeking a highly motivated candidate to contribute to the development of new catalytic systems through computational simulations and theoretical studies. Main Responsibilities: Perform computational
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-learning trained using the van der Waals corrected hybrid density functional theory (DFT) enabled SeA approach [J. Chem. Theory Comput. 19, 4182 (2023)]. The SeA approach is an accurate and efficient high
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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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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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techniques. The research will integrate ab initio-based modeling and DFT calculations with experimental data to enhance the understanding and optimization of the proposed materials as sorbents or possible
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simulation (classical and ab-initio molecular dynamics, DFT, simulations) Proficiency in programming languages like Python, C++, or Fortran for custom analysis tools. Experience in developing workflows