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Reinforcement learning for microbial strain design

Post-docoral researcher Maryam Sabzevari’s research deals with using artificial intelligence (AI) to design cell factories. Synthetic biology enables building of novel efficient production strains for desired products.

Modification of the microbial strain follows the DBTL cycle (Design, Build, Test, Learn), where the strain is computationally designed (D), built in a laboratory (B), measured and tested (T) using robotics, in order to learn (L) on the behaviour of the strain, to be exploited for the next cycle design phase (D) again. The design and learning phases still need significant computing solutions, which are the focus of Maryam’s research.


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