Description du sujet de thèse

DNA data storage is emerging as a interesting technology for archiving vast amounts of information in a highly compact, stable, and cost-effective format. However, there is still no mechanism for processing this data directly, without reverting it to digital form, a major barrier to large-scale adoption. This doctoral project paves the way for designing a DNA-based molecular computer capable of handling large-scale data processing. In contrast to fixed approaches inspired by Boolean or neural circuits, where all possible outputs are predefined (i.e., logic based on lookup tables), this project explores a shift toward an algorithmic paradigm, notably using Compact Labelling Schemes. This enables scalability, as the molecules executing the algorithm remain identical regardless of the input size, while also achieving exponential improvements in processing time.

However, algorithmic molecular programming presents new challenges. The large volume of data implies the presence of a vast number of DNA strands, each in very low concentration due to the requirements of massive synthesis. This dilution, combined with enzymatic detection limits, undermines the program's efficiency. The objective of this PhD project is to develop selective and controlled amplification methods to boost specific strands within a DNA library. This amplification will initially be performed using PCR, which requires the addition of primer sequences. To prevent these primers from interfering with the molecular program's operation, we will develop an enzymatic strategy to cleanly remove them using restriction enzymes, thereby restoring fully functional strands without compromising the system's integrity or efficiency.
By combining technological innovation and algorithmic foundations, this thesis aims to establish the basis for a new generation of molecular computing: scalable, programmable, and directly integrated with the DNA storage medium—opening new horizons in bioinformatics, personalized medicine, and ultra-long-term data archiving.

Contexte de travail

The successful candidate will be based at the IEMN (Institute of Electronics, Microelectronics and Nanotechnology UMR8520) in Villeneuve d'Ascq (University of Lille and CNRS), joining the BioMEMS group, an interdisciplinary team of around ten permanent researchers supported by eight PhD students and postdoctoral fellows within a larger institute of approximately 500 staff. At IEMN the candidate will benefit from state‑of‑the‑art cleanroom facilities, dedicated micro‑ and nanofabrication platforms, molecular biology and microfluidics laboratory and high‑resolution microscopy suites, enabling the candidate to design, fabricate and characterize DNA‑based nanodevices for molecular computing applications.

The candidate will also conduct research at LIMMS (Laboratory for Integrated Micro Mechatronic Systems, IRL2820), the CNRS–University of Tokyo international laboratory on the Komaba campus in Tokyo, where a team of about 16 permanent researchers, postdoctoral fellows and doctoral students collaborates on molecular and quantum technologies. At LIMMS the candidate will access cutting‑edge DNA nanotechnology laboratory and bio‑hybrid microsystem to develop and test programmable dynamic DNA architectures to explore novel schemes for DNA‑based data storage and computation in an international, multidisciplinary environment.

Le poste se situe dans un secteur relevant de la protection du potentiel scientifique et technique (PPST), et nécessite donc, conformément à la réglementation, que votre arrivée soit autorisée par l'autorité compétente du MESR.