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Field
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powerful, modern analytical techniques including chemical proteomics and metabolomics. They will have access to advanced synthesis facilities, as well as biological models, such as macrophages and organoids
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! You will demonstrated expertise in developing machine-learning interatomic potentials (MLIPs) for large-scale molecular dynamics (MD) simulations of materials. Together, we will push the boundaries
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MMGE - MOLECULAR GENETICS (IN-MOLG-IUINA) One of the first human genetics departments in the country, the Department of Medical and Molecular Genetics at IU School of Medicine has a rich history of
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these models to interpret experimental results from neural circuit perturbations Investigate the effects of altering neuronal dynamics on brain function and dysfunction Analysis of simulated or real population
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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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understanding of the molecular tools and analyses available to study protein pharmacology in the context of cell biology. Moreover, connecting and expanding these methods and concepts to other protein families is
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for Molecular Chemistry” to start as soon as possible. What you will do Literature research and identification of promising use cases for quantum computing in molecular chemistry Simulation of Hamiltonian
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their thermophysical properties. Proficiency in computational fluid dynamics (CFD) simulation of thermal energy storage systems, enabling the modeling and analysis of heat transfer, fluid flow, and thermodynamic
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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