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The vacancy is within the group of Prof. Barbro Melgert at the department of Molecular Pharmacology, Groningen Research Institute of Pharmacy, Faculty of Science and Engineering, University
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on molecular switches and motors, dynamic molecular systems, responsive materials, photopharmacology and biohybrid systems. The group also develops novel stereoselective synthesis methods and asymmetric
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-microbe growth experiments in controlled environments, with the flexibility to extend to field research. Background in microbiology and/or molecular techniques, including bioinformatics for DNA-based
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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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that are still largely controlled with insecticides. Alternative, more sustainable methods to combat these pest are desperately needed. Plants harbour diverse and dynamic microbial communities in and around their
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results, further research is guided by trial and error with the goal of deriving intuitive trends. Data-driven approaches are attractive alternatives. Descriptors are used to characterize the molecular
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to characterize the molecular properties of catalysts together with statistical methods to derive predictive models for selective catalysis. In a data-driven approach, an initial set of reactions is analyzed and