Digital representation of smell for food manufacturing process optimisation
Supervisors: Tanoj Singh (CSIRO), Chen Wang (CSIRO), Xavier Sirault (CSIRO), and Rod Peakall (ANU).
Recent research has shown that a method based on a graph neural network can learn a digital representation of smell from odorous molecules. This has potential to change food manufacturing processes by paving the way for optimized seed selection and protein fractionation to achieve desired food product properties.
The PhD candidate will study smell representations of molecules of interest and use these representations to develop an understanding of the biological foundation of odour perception and the robustness and generalizability of learned representations in handling unseen / novel molecules.
The generic digital approach developed for the representation of volatile organic compounds will be applicable to food manufacturing and wider biological research, namely pollination. The selected candidate will be carrying out research work both at CSIRO (laboratories at Black Mountain, Canberra and Melbourne) and ANU.