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of Biochemistry and Microbiology Degree You hold a Master’s degree (preferably) in Biochemistry, Biotechnology, Microbiology, Molecular Biology, Biomedical Sciences, or a closely related field. Occupancy rate 100
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researchers and students from around the world. With new knowledge and new perspectives, the University contributes to a better future. The Department of Chemistry and Molecular Biology conducts high-quality
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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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letter Current curriculum vitae Copy of PhD diploma A list of publications and conference presentations Signed information on the processing of personal data (https://bsp.adm.uw.edu.pl/wp-content/uploads
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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 | 9 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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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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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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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