Description du sujet de thèse

PhD position in Paleogenomics: Tracing Ecosystem Change through time (ANR-funded project PaleoGreen)

Agroecosystems play a vital economic role, yet they also exert a high environmental impact, contributing to pollution, biodiversity loss, greenhouse gas emissions, climate warming, and risks to human health. A key scientific challenge is to understand how biodiversity and ecosystem functions have shifted over time - from pristine natural conditions to the intensively managed agricultural landscapes of today.
Environmental ancient DNA (eaDNA) provides a powerful means to address this gap by reconstructing past ecosystems from genetic traces preserved in sediments. This approach offers unprecedented opportunities to reveal how human activities, including climate change, land-use change, pollution, and biodiversity loss, have shaped ecosystems in the Anthropocene.
Particular attention is directed to environmental microbiomes - the assemblages of bacteria, archaea, viruses, and fungi that drive ecological processes and sustain ecosystem health and services. Their interactions with plants and the environment, which have evolved over millennia, are now increasingly disrupted but can be traced through long-term monitoring. This PhD project will apply cutting-edge ancient DNA metagenomics and computational approaches to explore these dynamics, generating insights relevant for biodiversity conservation, ecosystem resilience, and sustainable agroecosystem management.

Activities :
• Perform DNA extraction from ancient sediment cores and prepare sequencing libraries for shotgun metagenomics in a dedicated paleogenetics laboratory.
• Participate in sequencing workflows and coordinate with sequencing facilities for data generation.
• Optimize laboratory protocols for ancient DNA recovery and library preparation.
• Process raw metagenomic data (quality control, filtering, and assembly) and carry out downstream analyses such as taxonomic profiling and functional annotation.
• Develop and adapt bioinformatic pipelines for paleogenomic data analysis.
• Apply advanced statistical and computational approaches (e.g., diversity metrics, ordination, network analysis) to interpret metagenomic data in the context of microbial ecology and past ecosystems.
• Present research findings at national and international conferences, workshops, and seminars.
• Contribute to the preparation of scientific publications in peer-reviewed journals.
• Maintain detailed laboratory notebooks, data records, and documentation to ensure reproducibility.
• Support the teaching, training, or mentoring of Master's students or interns where appropriate.

Skills :
• Molecular biology expertise: hands-on experience with DNA extraction, PCR, metagenomic sequencing, and downstream data analysis (taxonomic and functional annotation).
• Bioinformatics proficiency: ability to run and develop code in Python, R and similar tools.
• Good understanding of microbial ecology and its applications in ecosystem research.
• Previous experience with ancient DNA is desirable, but not necessary.
• Communication skills: excellent command of spoken and written English.
• Work style: capacity to work independently while demonstrating a strong ability to collaborate effectively within a team.

Contexte de travail

This PhD project is funded by the French National Research Agency (ANR) and supervised by Chair Professor Jr. Amedea Perfumo. Research activities will be carried out at the Chrono-Environnement laboratory (UMR 6249, Université Marie et Louis Pasteur, Besançon). Chrono-Environnement is a multidisciplinary research institute bringing together experts in ecology, paleo-environments, biodiversity, Earth sciences and archeology. Its teams investigate the interactions between environment, climate, and societies through experimental, observational, and modeling approaches.
The experimental work for this PhD will be conducted in the specialized facilities of the paleogenetic laboratory at Chrono-Environnement, which offers state-of-the-art infrastructure for ancient DNA research.