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, molecular dynamics, and machine learning, to model battery electrolyte and solid electrolyte interphase (SEI), while collaborating with experimentalists. Qualifications • Ph.D. in Computational Materials
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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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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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vegetables. Model bacterial pathogenic levels through complex survival and growth patterns. Utilize either data analysis or molecular analysis tools (or both) to inform strategies to optimize pre-harvest
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the area of fundamental modelling with molecular dynamic and ice/substrate interface bonding analysis. The main aspects of the research fellow role include conducting icing experiments in the Cranfield Icing
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group of A/Prof Patrick Burr, please visit https://www.patrickburr.com/group In your role you will be responsible for performing ab-initio and molecular dynamics simulations, and for developing inter
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: Quantum simulation with Rydberg atom arrays (theory) Research Area: Atomic, molecular, and optical physics (AMO), quantum control, quantum simulation Relevant Fields: Quantum information science, quantum
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: Quantum Simulation with Rydberg Atom Arrays (Experiment) Research Area: Atomic, molecular, and optical physics (AMO), quantum control, quantum simulation Relevant Fields: Quantum information science
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invites applicants for four PhD Fellowships in subsurface characterization within geosciences, reservoir engineering, molecular modelling, and machine learning at the Faculty of Science and Technology
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simulation or machine learning of soft and biological matter, e.g. Monte Carlo, molecular dynamics and finite element computer simulations. Origins of life research involving topology and chirality