Postdoctoral Research Fellow based in Montpellier, France
| Location | LEPSE – INRAE, Institut Agro, Montpellier, France Zenith – LIRMM, Inria, CNRS, Univ. Montpellier, France |
| Lab Website | https://www6.montpellier.inrae.fr/lepse_eng/ https://team.inria.fr/zenith/ |
| Date of Hire | As soon as possible |
| Duration | 18 Months |
| Gross annual salary | 42,672 – 49,248 € (commensurate with experience and qualification) |
JOB DESCRIPTION:
We are seeking an outstanding, motivated candidate with established prior experience in deep learning, computer vision, and ideally image tracking for an 18-months Post-Doctoral position in computer science.
You will work within an INRAE-INRIA-CIRAD collective of ecophysiologists, plant modelers and computer scientists in the frame of the PHENOME-EMPHASIS and EPPN2020 projects to produce a complete solution for the analysis of plant development and architecture. The research effort will focus on the development of time-series analyses of in situ 3D images to characterize the evolution of the spatial structure of plants over time (growth curve, shape evolution) and its modulation according to environmental conditions, in order to allow a genetic analysis of these differences and to retrieve the values of parameters of plant growth simulation models.
You will benefit from large datasets consisting in time series of annotated 3D wheat, maize, sorghum, and rice plant images acquired in the PhenoArch platform and processed with the Phenomenal processing chain. You will first develop algorithms from a set of wheat plant images obtained in two experiments where several water and nitrogen deficit treatments resulted in contrasted plant size and development and for which a number of properties were measured (leaf size, number of leaves, number of tillers….). In a second step, these data will be used to extend different plant growth and development models (e.g. ADEL, SiriusQuality).
As a postdoctoral researcher, you will be led to:
- Analyze a variety of 3D volumetric temporal data to generate estimates of plant development dynamics properties.
- Contribute to the development of new automatic data processing algorithms to match the different 3D plant acquisitions.
- Work as a member of a multidisciplinary research team.
- Write technical reports and write and publish articles in peer-reviewed journals.
Skills needed:
- Strong skills in image analysis and deep learning.
- Demonstrated experience in 2-D and 3-D image processing techniques or in a related field.
- Excellent programming skills: must be expert in Python, C and C++.
- Strong scientific knowledge in mathematics, imaging techniques or numerical modelling.
- Ability to creatively identify and solve problems, use observational data to improve models and implement alternative solutions.
- Ability to collaborate with a multidisciplinary team of scientists, and to write publications in English.
APPLICATION CONDITIONS:
Candidate of any nationality may apply. You must have a doctoral degree at recruitment date (French doctorate, PhD or foreign doctorate of equivalent level) for less than five years.
HOW TO APPLY:
To apply you should submit a letter of interest, complete CV, with a list of publications, the names and addresses (including telephone and email) of three referees who are knowledgeable about your professional qualifications and work experience, and relevant certificates.
For further information and to apply, please contact Antoine Liuktus (antoine.liutkus@inria.fr), Christophe Pradal: (christophe.pradal@inria.fr), and Christian Fournier (christian.fournier@inrae.fr).
This position will remain open until filled.
About Empleo ETSIAAB
Publicación realizada por la Oficina de Empleo de la Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas (ETSIAAB)
