PhD in super-resolution X-ray CT and multiscale modelling of horticultural products

(ref. BAP-2022-456)

Laatst aangepast : 27/06/2022

The lab of Prof. Nicolai consists of a team of young, dynamic and enthusiastic researchers that investigate processes and technology for improving quality of horticultural products such as fruit and vegetables, , with a strong engineering approach. We offer a stimulating work environment for those who are interested in scientific research on the verge of fundamental and applied research, with a high relevance to making a more sustainable world. KU Leuven is a world-class university and ranked 42 on the Times Higher Education World University Rankings, and ranks 7 on Reuters Most Innovative Universities Worldwide (being No. 1 in Europe).

Project

Horticultural products such as fruit are composed of different tissues, composed of cells and intercellular spaces. Fruit tissues are very heterogenous at the micro scale and the microscopic architecture determines to a large extent the fruit response to postharvest storage conditions that are aimed to control a minimal respiration rate of the fruit by modifying O2 and CO2 gas concentrations. As there are currently few experimental methods available to investigate in vivo respiratory gas transport processes at the cellular level of fruit, in silico modelling is essential. In this context, resolving the three-dimensional microstructure and its distribution across the fruit is required for simulating respiratory gas exchange in fruit. Visualization of the 3D fruit microstructure can be achieved by non-destructive imaging methods, such as X-ray computed tomography. However, the cost and effort to obtain sufficiently high image resolution of the porous microstructure, and capture the spatial heterogeneity of the microstructure across a fruit is large. Today, multiscale modelling is applied, in which effective transport parameters of the macroscale fruit model are calculated from simulations with a limited number of representative microscale tissue models obtained from high resolution X-ray CT, in which the spatial heterogeneity is parameterized based on, for example, porosity maps. In this PhD project, you will investigate alternative approaches that can effectively resolve the spatial heterogeneity using super-resolution deep learning methods applied to low resolution images of intact fruit. In addition, you will develop and apply more efficient models, such as pore network and lattice-Boltzmann methods to solve the respiration-diffusion problem at the microscale of the porous tissues.

Profile

The lab is looking for a highly motivated PhD candidate who is eager to become part of a highly visible international interdisciplinary team to perform cutting-edge research. You have a critical mind and you have good affinity with advanced image analysis, algorithm programming and heat and mass transfer modelling. You are required to have a Master of Science degree (or equivalent) in (bioscience) engineering, physics or mathematics.

Offer

The lab offers you a 4 year PhD position. The lab will support you in all aspects in order to successfully obtain a PhD degree and a proper scientific training. You will be given opportunities to participate at national and international meetings and establish your own network. You will have an advanced training in postharvest technology, X-ray CT, image analysis and numerical modelling techniques and work closely with application experts. You will have also great opportunities to gain experience in transferal skills.

Interested?

For more information please contact Dr. ir. Pieter Verboven, tel.: +32 16 32 14 53, mail: [email protected] or Prof. dr. ir. Bart Nicolai, tel.: +32 16 32 23 75, mail: [email protected].

KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at [email protected].