PhD Position F/M RobDNA:Robust data retrieval for DNA-based data storage

PhD Position F/M RobDNA:Robust data retrieval for DNA-based data storage Download job offer in PDF format Contract type : Fixed-term contract Level of qualifications required : Graduate degree or equivalent Fonction : PhD Position About the research centre or Inria department The Inria Centre at Rennes University is one of Inria's nine centres and has more than thirty research teams. The Inria Centre is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc. Context Context The volume of data generated worldwide is projected to approach 180 zettabytes (ZB) per year by 2025 [1]. However, current storage technologies face significant limitations in scaling sustainably to such volumes. One promising solution to address these challenges is DNA-based data storage, which offers several advantages, including extremely high data density, long-term retention, and low energy consumption [2]. From a density perspective, DNA can theoretically store up to 10 terabytes per mm³, which would allow all data generated throughout human history to be stored within a cube of approximately 30 cm per side [3]. In terms of retention, DNA can remain readable for centuries under suitable conditions, whereas conventional storage media typically degrade within decades [3]. Furthermore, DNA storage is energy-efficient, as it can be preserved at ambient temperature provided it is protected from light and humidity. Assignment Goal The goal of the project is to develop an algorithm to allow robust retrieval of data in the context of DNA-based data storage. Main activities Challenges and envisaged approach Despite its potential, making DNA a practical and efficient storage medium requires overcoming several key challenges: (i) Data transformation: converting digital data into a quaternary alphabet (A, C, G, T). (ii) DNA synthesis: writing data through the physical synthesis of DNA strands. (iii) DNA sequencing: reading the stored data by sequencing DNA. (iv) Data retrieval: reconstructing the original digital data from the sequenced symbols. This PhD project focuses on the first and fourth challenges, by developing joint compression and error-correction algorithms that are robust to sequencing errors arising during step (iii). Efficient DNA storage critically depends on fast sequencing technologies, which often come at the cost of increased error rates. For example, nanopore sequencing, developed by Oxford Nanopore Technologies (ONT), enables real-time analysis but introduces relatively high error rates [4,5]. Unlike traditional sequencing technologies, nanopore sequencing produces not only substitution errors but also insertion and deletion errors. Deletions are particularly challenging, as they differ from erasure errors where the position of missing data is known e.g., packet losses in digital communications). In the case of deletions, neither the existence nor the location of the missing symbols is known, significantly complicating error correction. Two main approaches have been proposed in the literature to address these errors. The first consists of avoiding error-prone patterns by designing constrained DNA sequences, such as limiting homopolymers or enforcing balanced GC content [6]. The second approach embraces sequencing errors and focuses on correcting them using coding techniques [7]. These strategies are typically considered contradictory, as one seeks to prevent errors while the other assumes their presence [8]. In this project, we propose to explore an alternative route that combines both strategies: avoiding the majority of sequencing errors while correcting the remaining ones. This will be achieved by jointly structuring the compressed DNA stream and designing error-correction mechanisms tailored to nanopore sequencing. In particular, we will exploit the properties of the quaternary alphabet and the interaction between compression and error-correction algorithms. The work will build upon concepts from non-binary channel coding [10,11] and DNA-specific transcoding techniques [6], while also integrating efficient post-sequencing data retrieval methods such as those proposed in [9]. Bibliography [1] David Reinsel-John Gantz-John Rydning, John Reinsel, and John Gantz. “The digitization of the world from edge to core.Framingham: International Data Corporation”, 16:1–28, 2018. [2] Luis Ceze, Jeff Nivala, and Karin Strauss. “Molecular digital data storage using DNA”. NatureReviews Genetics, 20(8):456–466, 2019. [3] Victor Zhirnov, Reza M Zadegan, Gurtej S Sandhu, George M Church, and William L Hughes. “Nucleic acid memory”. Nature materials, 15(4):366–370, 2016. [4] Delahaye, Clara, and Jacques Nicolas. “Nanopore MinION Long Read Sequencer: An Overview of Its Error Landscape,” November 23, 2020. https://hal.inria.fr/hal-03123133. [5] ———. “Sequencing DNA with Nanopores: Troubles and Biases.” PLoS ONE, October 1, 202 [6] S. Al Sayyed and A. Roumy and T. Maugey. ``Efficient constraining of transcoding for DNA-based data storage'', IEEE International Conference on Image Processing (ICIP), 2025. [7] R. Khabbaz, M. Antonini, S. Kas Hanna, Marker Guess & Check Plus (MGC+): An Efficient Short Blocklength Code for Random Edit Errors, International Symposium on Topics in Coding (ISTC), 2025. [8] F. Weindel, A. L. Gimpel, R. N. Grass and R. Heckel, ”Embracing errors is more effective than avoiding them through constrained coding for DNA data storage,” Allerton Conference on Communication, Control, and Computing 2023. [9] F. De Moor, O. Boullé, D. Lavenier, De Bruijn Graph Partitioning for Scalable and Accurate DNA Storage Processing, BioRxiv, 2025. [10] M. C. Davey and D. J. C. Mackay, “Low density parity check codes over GF(q)”, Information Theory Workshop, 1998, pp. 70-71. [11] D. Declercq and M. Fossorier, “Decoding algorithms for nonbinary LDPC codes over GF(q)”, IEEE Trans. on Commun., vol. 55, pp. 633- 643, April 2007 Benefits package • Subsidized meals • Partial reimbursement of public transport costs • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.) • Possibility of teleworking (after 6 months of employment) and flexible organization of working hours • Professional equipment available (videoconferencing, loan of computer equipment, etc.) • Social, cultural and sports events and activities • Access to vocational training • Social security coverage Remuneration 2 300€ per month Apply for this position Share • Facebook • Linkedin • Twitter • Email General Information • Theme/Domain : Vision, perception and multimedia interpretation Information system (BAP E) • Town/city : Rennes • Inria Center : Centre Inria de l'Université de Rennes • Starting date : 2026-12-01 • Duration of contract : 3 years • Deadline to apply : 2026-11-20 Warning : you must enter your e-mail address in order to save your application to Inria. Applications must be submitted online on the Inria website. Processing of applications sent from other channels is not guaranteed. Instruction to apply Please submit online : your resume, cover letter and letters of recommendation eventually Defence Security : This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST).Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment. Recruitment Policy : As part of its diversity policy, all Inria positions are accessible to people with disabilities. Contacts • Inria Team : COMPACT • PhD Supervisor : Roumy Aline / aline.roumy@inria.fr The keys to success Candidate profile The candidate should have • strong background in image/signal processing, optimization and programming, • notions of source coding, information theory would be appreciated. About Inria Inria, the French national institute for research in digital science and technology, supports the French government in national research and innovation strategies in the digital field, acting as Digital Programs Agency. Inria leads over 300 research and innovation projects with its 3,500 scientists, engineers, and support staff, in partnership with universities and the digital ecosystem (businesses, entrepreneurs, and public stakeholders). Together, we explore strategic fields such as artificial intelligence, cybersecurity, quantum computing, cloud technologies, digital transformation in healthcare, digital twins, and digital technologies for defence. We develop practical solutions such as software, tech startups, partnerships with national companies, and cutting-edge training programmes. Our goal is to drive scientific, technological, and industrial excellence to ensure France’s digital sovereignty.