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papers and reports. We are looking for: Ph.D. in Chemistry/Physics/Materials Science, or similar fields. Density Functional Theory, Molecular Dynamics (ab-initio MD and/or nonadiabatic MD), Kinetic
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to scientific research papers and reports. We are looking for: Ph.D. in Chemistry/Physics/Materials Science, or similar fields. Density Functional Theory, Molecular Dynamics (ab-initio MD and/or nonadiabatic MD
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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
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engineering, chemistry, physics, or a closely related field are particularly encouraged to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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. Quantum Mechanical Calculations: - Performing first-principles based or Density Functional Theory (DFT) calculations for molecules/materials and interphases - Utilizing Molecular Dynamics (MD) simulations
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leveraging AI, quantum chemistry, and molecular dynamics simulations. The candidate will work in close collaboration with experimental groups providing validation/testing of novel mixed conducting materials
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or equivalent. 2. Demonstrable experience in either atomistic molecular dynamics simulations or quantum chemistry/density functional theory calculations 3. Demonstrable programming skills 4. Strong
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strongly recommended. • High Performance Computing. • Experience with High Throughput Calculations will be valued but it is not essential. • Previous knowledge of Density Functional Theory (DFT) and
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in Journal Citation Indexed (JCR) journals. Qualification or experience in any of the following disciplines: Life Cycle Assessment, Density Functional Theory or Materials Experimentation