Offre en lien avec l’Action/le Réseau : – — –/Doctorants

Laboratoire/Entreprise : University of Murdoch (Australia) – Tetis (Montpel
Durée : 36
Contact : maguelonne.teisseire@teledetection.fr
Date limite de publication : 2023-09-30

Contexte :
Joint PhD position
Data-Driven Methods for Modeling the 3D Structure of Plants

Sujet :
The aim of this PhD thesis is to develop data-driven techniques for modelling the 3D structure of plants and analyze how plant structure is affected by various intrinsic and extrinsic factors such as soil conditions and environmental factors. This is an important problem that has a wide range of applications in plant biology and agriculture. One of the main scientific challenges is to develop efficient algorithms for the extraction of features and patterns from 3D point clouds representing plant shape. Another challenge is to develop models that can simulate the growth and development of plant structures over time, taking into account various environmental factors. Another scientific question addressed in this project is how to analyze the complex relationships between plant structure and function at different scales. This involves the development of methods to measure and quantify plant traits such as biomass, leaf area, and stomatal density, and to relate these traits to plant function and performance. Overall, the project aims to advance our understanding of the structure-function relationships in plants and to provide new tools for plant breeders, ecologists, and agronomists to improve crop productivity and resilience in the face of environmental challenges.
Keywords: Deep Learning, 3D computer vision, shape analysis, geometric modelling.

Profil du candidat :
Qualification: The successful candidate is expected to have a MSc degree (or equivalent), with a significant research component, completed by September 2023, with background in either image processing, computer vision, computer graphics, machine learning applied for vision, or 3D geometry processing. Students with background in mathematics, especially 3D geometry, are highly encouraged to apply.

Formation et compétences requises :

Experience: The ideal candidate should have some knowledge and experience in at least one of the fields listed above. The successful candidate should have strong programming skills.

As for generic competences, we seek a qualified self-motivated professional, open to multidisciplinary, with capacity to undertake independent research, ability to work in a teamwork, and self-motivated.

Language Skills: Fluent written and verbal communication skills in English are required.

Adresse d’emploi :
The candidate should also be willing to spend 18 months in Australia and 18 months in France.

Document attaché : 202307101258_TETIS_Murdoch_Joint_PhD_position_2023.docx – Google Docs.pdf