Job offer

The global production of digital data is growing exponentially, posing a significant challenge to available storage capacities. Despite advances in density and cost per gigabyte, conventional storage media face limitations in terms of energy efficiency, sustainability, cost, and environmental impact.

In this context, digital data storage in DNA emerges as a promising technology, particularly for long-term archiving. DNA offers an extremely high theoretical information density, on the order of 10¹ bits per mm³, as well as excellent stability when stored under appropriate conditions. These properties could enable the storage of large amounts of data in a compact and durable form, with limited maintenance and energy requirements during the preservation phase.

A DNA-based storage system relies on a series of steps: (1) encoding digital data into nucleotide sequences, (2) synthesizing or constructing DNA molecules corresponding to data writing, (3) preserving the molecules, (4) retrieving the molecules containing the desired information, (5) sequencing them, corresponding to data reading, and (6) decoding the obtained sequences to reconstruct the digital data. Significant progress has been made on each of these steps over the past decade. However, their large-scale implementation still faces several scientific and technological challenges.

THESIS OBJECTIVES

These challenges cannot be addressed by a single approach: they require multiple complementary technological components, covering different stages of DNA storage.

This thesis will focus on the biotechnological aspects of molecular storage, specifically steps 2 to 5 described above. It will build on the work of the GenScale team (IRISA, Rennes) and on collaborations with the CompACT team (IRISA, Rennes), CYBERHEALTH (IMT Atlantique, Brest), and LIMMS (CNRS/Institute of Industrial Science, Tokyo).

The goal will be to develop and experimentally validate methods intended for integration into future DNA-based digital storage systems.

Research Field Computer science

Education Level PhD or equivalent

Research Field Mathematics

This thesis is part of the exploratory PEPR MoleculArXiv, a national program funded by France 2030 and led by the CNRS. Its aim is to design new devices for massive data storage on molecular media (PEPR MoleculArXiv). The PhD student will be hosted in the GenScale team at IRISA in Rennes and will collaborate with LIMMS, the CNRS international laboratory based in Tokyo.