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Simulation group to apply classical Molecular Dynamics and Machine Learning approaches for development of a new class of hybrid polyphenol-lipid nanoparticles with tuneable internal structure and exploration
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integrated research in computational, information and experimental sciences. (1) Development of molecular dynamics simulation model of network formation by free radical polymerization in an extension
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). • Required Skills: 1. Strong background in statistical mechanics and thermodynamics 2. Proficiency in first-principles calculations (VASP, Quantum Espresso) and molecular dynamics simulations (LAMMPS, OpenMM
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, Physics, Computer Science, or a related field. Hands-on experience with computational materials methods (e.g., DFT, molecular dynamics, machine learning force field simulations). Proficiency in Python
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Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT's Materials Modelling and Simulation group to apply classical Molecular Dynamics and Machine Learning approaches
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at the RMIT Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT’s Materials Modelling and Simulation group to apply classical Molecular Dynamics and Machine Learning
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Date of Assignment, Project, or Grant) 08/15/2026 Position Type Faculty Job Family Faculty Position Overview This postdoctoral appointment in theoretical and computational chemistry/molecular physics
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. However, most studies to date have focused on symmetric bilayers. This project addresses this gap by integrating molecular dynamics simulations with experimental techniques such as solid-state NMR
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for pathogenic microorganisms. Molecular biology skills sufficient to characterize the microbial community present in dynamic settings both qualitatively and quantitatively. Bioinformatic and genomic analysis
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physics, physical chemistry, computational chemistry, statistical mechanics, or related fields Experience with molecular dynamics simulations (with GROMACS, OPENMM, LAMMPS, NAMD, AMBER, etc