PhD Position: Machine learning assisted design of heteromeric self-assembled molecular capsules (P1906)

Your position

Catalysis in hydrogen bond-based supramolecular capsules is the main research direction in the Tiefenbacher group. Much like enzymes, such capsules feature a nanometer-sized cavity where suitable reactions can be accelerated due to noncovalent interactions between the substrate and host. Interesting results concerning complex terpene cyclizations, which were inaccessible with man made catalysts before, have been obtained in our laboratory (for more information see: https://nanocat.chemie.unibas.ch/en/research/). Although these examples clearly demonstrated the potential of this approach, selectivity issues remain. Due to the high symmetry of the nanometer sized reaction compartment on the inside of the molecular capsule, the conformation of the flexible acyclic terpene substrates cannot be controlled well. The floppy binding translates into a poor selectivity during terpene cyclizations. To achieve selective cyclizations for biologically relevant sesqui- and diterpenes, less symmetric cavities, able to constrain the conformationally freedom of the encapsulated the substrate, are required.
The overall aim of this project is the discovery of novel heteromeric self-assembled molecular capsules suitable for selective sesqui- and diterpene cyclizations. Since there is no rational approach available, we aim for a broad screening approach aided by machine learning algorithms developed in the von Lilienfeld lab (for more information see: https://chemspacelab.org/ ).

Your profile

We are looking for a very motivated researcher with a Master's degree in Natural Sciences, with a strong background in organic synthesis and programming. The project also requires the abilities to work independently, interact with other researchers, presentation skills, and a solid basis in scientific research.

We offer you

• Excellent scientific and social environment
• Very competitive employment conditions
• Membership in a very supportive and recognised community

The successful candidate will join an attractive interdisciplinary PhD programme together with the ~30 currently supported scientists. The SNI covers a wide variety of topics, including cutting edge quantum physics and chemistry, material science, nanotechnology, biochemistry, cell biology, or medical research.