PhD Student in Extrachromosomal DNA Dynamics and Cellular Rejuvenation
Explore the transmission of extrachromosomal DNA (ecDNA) and its role in cellular aging using yeast models and quantitative imaging.
Best for:Best for life science researchers with expertise in yeast genetics, quantitative microscopy, and computational data analysis seeking a multidisciplinary PhD in cellular aging and genomic instability.
Overview
This PhD position at the CNRS in Strasbourg focuses on understanding how genomic instability is confined within cells and transmitted across generations. The project investigates the dynamics of extrachromosomal DNA (ecDNA) in *Saccharomyces cerevisiae*, particularly how its asymmetric distribution during cell division impacts cellular rejuvenation. The candidate will conduct long-term microfluidic experiments, fluorescence microscopy, yeast genetics, and quantitative data analysis to study ecDNA formation, retention, and transmission. The work integrates experimental biology with computational modeling, statistical analysis, and image processing, bridging cell biology, genetics, and biophysics. The project is funded by the ANR REJUVENATE programme and hosted in a multidisciplinary lab at the École supérieure de biotechnologie de Strasbourg.
What you'll do
- Conduct long-term microfluidic experiments and live-cell fluorescence microscopy to study ecDNA dynamics in *Saccharomyces cerevisiae*.
- Implement yeast genetic approaches and inducible ecDNA formation systems to manipulate and quantify ecDNA behavior.
- Measure ecDNA formation, amplification, retention, and asymmetric transmission between mother and daughter cells.
- Assess the impact of ecDNA transmission on daughter cell rejuvenation and replicative lifespan.
- Characterize chromosomal segregation using imaging and targeted genomic analyses.
- Develop and apply automated image analysis and lineage-tracking methods for high-throughput data processing.
- Integrate experimental data with statistical analysis, probabilistic inference, and quantitative modeling.
- Collaborate across disciplines (cell biology, genetics, biophysics, and computational science) to interpret results.
- Present findings at scientific conferences and publish in international journals.
- Document and share computational tools and analytical methods in line with open science principles.
Requirements
Degree required: Master's degree (or equivalent) in Life Sciences, Genetics, Cell Biology, Biophysics, or a related field.
Degree offered: PhD
Language: Fluent English (scientific writing/communication); French proficiency is not required but may be helpful for local integration.
Instruction: English (for thesis and supervision); French may be used in lab contexts.
- Hands-on experience with yeast (*Saccharomyces cerevisiae*) genetics and molecular biology techniques.
- Proficiency in fluorescence microscopy and image analysis (e.g., Fiji/ImageJ, Python/R for data processing).
- Familiarity with microfluidic systems and long-term cell culture techniques.
- Experience with quantitative data analysis, statistical modeling, or computational biology (e.g., Bayesian methods, probabilistic inference).
- Strong laboratory skills in molecular cloning, PCR, and genomic analyses.
- No nationality restrictions (CNRS open to international applicants).
- Admission to the École doctorale des Sciences de la Vie et de la Santé (ED 414) at Université de Strasbourg is mandatory.
- Applicants must complete CNRS administrative onboarding procedures.
Funding & terms
How to apply
Deadline: 2026-10-29
Applicants must submit a CV, cover letter, academic transcripts, and a research proposal outlining their interest in the project. Additional documents may include letters of recommendation and proof of eligibility for PhD admission at Université de Strasbourg. Applications are reviewed by the lab and CNRS admissions committee.
- CV
- Cover letter
- Academic transcripts (BSc + MSc)
- Research proposal (1-2 pages)
- Letters of recommendation (2-3)
- Proof of eligibility for PhD admission (ED 414)
Contact
Gilles Charvin· PhD Supervisor
Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.