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modelling of materials and machine learning. Experience in atomistic modelling (molecular dynamics, density functional theory) and machine learning is important, as well as a strong interest in pursuing
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dynamics of plasmid copy number in pathogenic bacteria, with a strong focus on infection biology and evolution of antibiotic resistance. The goals for this project are i) to better understand the role
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implementation is advantageous (especially if in the context of protein structure) Experience with structural biology and/or molecular dynamics is advantageous Publicly available code is advantageous Experience
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of computational chemistry. Applicants can have a background from cheminformatics including RDKit, machine learning applied to chemistry, and molecular modeling Our group and research- and what do we offer? Our