Building a differentiable AI model of apple tissues

About the project

About the Project This project aims to develop a fully differentiable, physics-based digital twin of apple tissue that links microstructural, biochemical, and mechanical processes to macroscopic fruit quality outcomes. By integrating artificial intelligence with computational solid mechanics and post-harvest biology, the project will establish a new modelling paradigm for predicting and optimising the mechanical integrity of fleshy fruit during storage and transport. At its core, the research will combine differentiable physics frameworks (e.g., JAX-FEM) with advanced machine learning approaches such as Fourier Neural Operators to overcome key limitations of traditional finite element modelling. The project will leverage statistical microCT-derived surrogate meshes to represent tissue microstructure, enabling efficient, resolution-invariant simulations. These models will be trained to infer relationships between biochemical markers (e.g., ATR-FTIR measurements) and mechanical properties, thereby providing a mechanistic bridge between cellular-scale processes and bulk fracture behaviour. A central objective is to solve challenging inverse problems in biomechanics, allowing the model to predict how internal tissue properties evolve under different post-harvest conditions. In particular, the research will focus on simulating the effects of interventions such as controlled atmosphere storage and 1-MCP treatment on cellular degradation and softening processes. By embedding uncertainty quantification within a probabilistic modelling framework, the digital twin will support robust predictions of fruit firmness, failure, and shelf-life. The expected outcome is a scalable and deployable simulation tool capable of replacing computational bottlenecks associated with conventional modelling approaches. Beyond advancing fundamental understanding of plant tissue biomechanics, the project will deliver practical impact by enabling data-driven optimisation of post-harvest handling and global horticultural supply chains. Overall, this interdisciplinary project sits at the interface of bioengineering, applied mathematics, and machine learning, offering a unique opportunity to develop next-generation modelling tools for complex biological systems. Desired skills A strong academic background (Honours or Master’s degree) in Bioengineering, Computational Mechanics, Computer Science, Applied Mathematics, or a closely related quantitative discipline. Demonstrable proficiency in scientific programming using Python. Solid understanding of continuum mechanics, solid mechanics, or finite element analysis. Strong analytical and problem-solving skills, with the ability to work rigorously on complex, multidisciplinary problems. Excellent written and verbal communication skills, with the ability to engage across engineering, computational, and biological domains. Find out more about this project and other projects on our website here. The Auckland Bioengineering Institute - breaking boundaries in bioengineering for more than 20 years At the Auckland Bioengineering Institute (ABI), we apply engineering and technical innovation to advancing medical care, human capability, and understanding of human physiology. Our team of world-renowned researchers are working on everything from artificial intelligence avatars, to implantable devices, to digital models of the human body. Our focus on research excellence and commercialisation adds value to society and to the global economy. Our research makes a real difference in the world. We’ve designed sensors to diagnose stomach disease without needing invasive surgery; developed a tiny wireless implantable device to measure brain pressure and save the lives of children with hydrocephalus; and we lead the world in building digital models of the human body which will enhance personalised medicine approaches for improved diagnosis and treatment. Join our team of researchers for a postgraduate degree and together we can make a difference. Our graduates are amongst the most employable in the world - many either continue their career in research, find employment with industry leaders such as Rocket Lab or Fisher & Paykel, or launch their own startup companies. Our students come from over 50 different countries and a wide range of backgrounds and disciplines, including Engineering, Medicine, Mathematics and Science. Want to know what our students think about studying at the ABI? Watch this video!

Research areas