David Rousseau is seeking a fellow for MSCA PF 2026 in Plant phenotyping through multi-source s[...]

Overview

Organisation / Company Université d'Angers Department Direction de la Recherche - Cellule Europe Laboratory Laboratory for Research in Systems Engineering Is the Hosting related to staff position within a Research Infrastructure? No

About LARIS

The LARIS laboratory (Laboratoire Angevin de Recherche en Ingénierie des Systèmes) at the University of Angers is a multidisciplinary research center specializing in systems engineering, control, data science, signal processing, and optimization . It develops advanced methodologies for modeling, decision support, artificial intelligence , and the engineering of complex socio-technical systems, with strong industrial and clinical partnerships. LARIS provides a dynamic and collaborative research environment, well suited for a Marie Skłodowska‑Curie postdoctoral exchange focused on methodological innovation and real‑world applications.

Project Description

This project aims to develop an integrated framework for high‑throughput plant phenotyping by combining multi‑source data from proximal sensors, satellite imagery, and embedded artificial intelligence. Modern agriculture faces the dual challenge of increasing productivity while reducing environmental impact, which requires precise, scalable, and real‑time monitoring of plant traits. The proposed research will focus on developing new methodologies to fuse heterogeneous datasets—such as field sensor networks, hyperspectral or RGB‑Depth, and remote‑sensing products—using advanced machine learning and edge‑computing techniques. By deploying embedded AI models directly on sensing devices, the project seeks to enable autonomous, low‑latency phenotyping in field conditions.

Hosted by Professor Rousseau’s group at the Université d'Angers, France (Imaging for Horticulture and Phenotyping) , which is internationally recognized for its expertise in high‑throughput phenotyping and digital agriculture, the postdoctoral researcher will benefit from a multidisciplinary environment bridging plant science, data science, and artificial intelligence. The expected outcome is a scalable and interoperable platform that enhances the accuracy and timeliness of phenotypic data collection for research and breeding programs.

Keywords

Deep learning, Imaging, life science application

Applicants must comply with the mobility rule: having stay in France less than 12 months in the past 3 years before the 9th of September 2026.

Applicants also must have maximum 8 years of research experience after graduating their (first) PhD.

A dedicated support programme will be offered to the selected fellow with online training, webinars, proofreading as well as a potential funding of mobility in Angers during 3 days for dedicated writing sessions.