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of Artificial intelligence for De-Novo molecular design Machine learning/Neuronal networks to develop novel drug discovery tools Molecular modeling and simulation Theoretical biophysical medicinal chemistry Deep
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 7 days ago
No. 24-11388I - Magneto-elasticity of non-cubic materials in spin-lattice dynamic simulations. Activity description: · conduct scientific investigations in two primary research directions: - development
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descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated
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sustainability. We develop functional fiber materials with specific photonic and electronic properties by polymer molecular engineering and fiber structure design. Together with advanced textile technology
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measure their mechanical, adhesive and frictional properties. By combining these data with classical molecular dynamics simulations and a molecular-scale approach to the thermodynamics of molecular
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underlying these processes remain poorly represented. This PhD project aims to fill that gap by using molecular simulations to quantify the interactions of SOM and EPS with water and minerals, and to connect
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differential equation models of bacterial persistence. A particular challenge, both for simulation and for machine learning, lies in the high dimensionality of these equations, which causes grid-based numerical
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. Description: Context: Laboratory Astrophysics is a core capability at NASA Ames Research Center. Laboratory experiments and quantum-chemical computations simulating astrophysical conditions generate data
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://www.mbnresearch.com ) is internationally recognised as a leading expert in the multiscale theory and simulations of molecular and condensed matter systems exposed to radiation, the development of advanced computational
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” led by Prof. Rafał Szabla. This project focuses on understanding the mechanistic aspects of nonenzymatic RNA self-replication using methods of molecular dynamics and quantum chemistry. In particular