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Innovator with the ambition to make genetically programming cells a reality in the true sense of the word programming, by predicting how changes to the genetic code of a cell will affect its behaviour. Pioneer in the development of programming languages for molecular and genetic circuits, which automatically generate computational models of behaviour from annotated DNA sequences.
Leader in Synthetic Biology with experience leading high-performing multidisciplinary teams at the intersection of computational modelling, lab automation and machine learning. Led research on learning computational models of cell dynamics from experimental data and on predicting interactions between DNA molecules from sequence.
Inspired by the potential of combining machine learning methods with domain knowledge in the form of automatically generated computational models, to predict the behaviour of a cell from changes to its genetic code.
Leader in Synthetic Biology with experience leading high-performing multidisciplinary teams at the intersection of computational modelling, lab automation and machine learning. Led research on learning computational models of cell dynamics from experimental data and on predicting interactions between DNA molecules from sequence.
Inspired by the potential of combining machine learning methods with domain knowledge in the form of automatically generated computational models, to predict the behaviour of a cell from changes to its genetic code.
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