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Field
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. Experience in asymmetric synthesis and the determination of enantiomeric excess. 2. Experience in using/applying density functional theory (DFT) 3. Evidence of independent funding
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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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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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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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related field Preferred Qualifications: Expertise in quantum chemistry of biomolecular or metal-coordination systems Experience with DFT, correlated wavefunction methods (e.g., MP2, CCSD(T)), and/or
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the development of hierarchical computational materials discovery schemes combining random structure searching, machine learning, atomistic, and density functional theory (DFT) calculations to accurately and
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(e.g., DFT modelling), or solid-state NMR spectroscopy. Excellent communication skills, a collaborative approach, and the ability to work independently are also key requirements for this position. A
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(e.g., DFT modelling), or solid-state NMR spectroscopy. Excellent communication skills, a collaborative approach, and the ability to work independently are also key requirements for this position. A
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yield optimization. Exposure to quantum chemistry (DFT) and molecular simulations is a plus. Experience with cloud computing and/or high-performance computing (HPC) resources. Application Process