Type de contrat : CDD
Niveau de diplôme exigé : Bac + 5 ou équivalent
Fonction : Doctorant
The Inria center at the University of Rennes is one of eight Inria centers and has more than thirty research teams. The Inria center is a major and recognized player in the field of digital sciences. It is at the heart of a rich ecosystem of R&D and innovation, including highly innovative SMEs, large industrial groups, competitiveness clusters, research and higher education institutions, centers of excellence, and technological research institutes.
Disclaimer
A PhD is not a continuation of coursework or a natural next step after a Master’s degree. A PhD is a long-term, research-focused commitment that requires deep curiosity, self-motivation, resilience, and a certain degree of autonomy.
By research, we mean creating new knowledge, not just applying existing theories. Your task is to discover, design, or prove something that no one has done before, work that will become what future students study.
If you are mainly looking for structured classes, predefined assignments, or a repeat of your Master’s experience, you will likely find this path unfulfilling. We welcome applications from candidates who are excited by uncertainty, driven to ask original questions, and eager to shape the frontier of their field.
Context and Background
The primary objective of this thesis is to investigate and advance the design of energy-efficient AI accelerators by dynamically applying approximate computing techniques and to advance hardware-software co-design methodologies.
The research will build upon recent advancements in efficient domain-specific architectures for AI. The goal is to develop novel approaches that balance performance, energy efficiency, and accuracy, while addressing the unique challenges of implementing approximate computing in real-world AI systems.
This research explores the principles and practical implications of approximate computing as a pathway toward more energy-efficient AI hardware accelerators. It examines how different forms of approximation affect computational efficiency, prediction accuracy, and overall system-level performance. Rather than treating these techniques in isolation, the study considers their combined impact across the computing stack, with particular attention to how accuracy-efficiency trade-offs can be characterized and controlled.
A central theme of the work is the integration of hardware and software perspectives through a co-design approach. By closely aligning algorithmic characteristics with architectural features, the research aims to uncover strategies for embedding approximation mechanisms directly into accelerator designs. Emphasis is placed on adaptive and context-aware approximation techniques that can dynamically balance energy savings and output quality, ensuring that efficiency gains do not compromise application-level requirements.
To ground these ideas in practice, the research involves modeling, simulation, and experimental prototyping using representative AI workloads, including deep learning inference and computer vision applications. Through systematic evaluation and validation, the study aims to assess the feasibility, robustness, and scalability of proposed approaches, contributing insights into the design of next-generation energy-efficient AI systems.
We seek highly motivated and passionate candidates. Autonomy is a highly appreciated quality.
Candidates should possess the following qualifications:
Candidates must have a Master’s degree (or equivalent) in Computer Engineering or related areas relevant to the PhD topic.
Talented last year Master’s students may start as 6-month interns and continue as Ph.D. researchers after graduation.
monthly gross salary 2300 euros
Attention: Les candidatures doivent être déposées en ligne sur le site Inria. Le traitement des candidatures adressées par d'autres canaux n'est pas garanti.
Please submit online : your resume, cover letter and letters of recommendation eventually
Sécurité défense :
Ce poste est susceptible d’être affecté dans une zone à régime restrictif (ZRR), telle que définie dans le décret n°2011-1425 relatif à la protection du potentiel scientifique et technique de la nation (PPST). L’autorisation d’accès à une zone est délivrée par le chef d’établissement, après avis ministériel favorable, tel que défini dans l’arrêté du 03 juillet 2012, relatif à la PPST. Un avis ministériel défavorable pour un poste affecté dans une ZRR aurait pour conséquence l’annulation du recrutement.
Politique de recrutement :
Dans le cadre de sa politique diversité, tous les postes Inria sont accessibles aux personnes en situation de handicap.
Candidates with knowledge and experience in at least one of the following areas are highly valued: Hardware Design, Hardware/Software co-design.
We seek highly motivated and passionate candidates. Autonomy is a highly appreciated quality.
Essential qualities to fulfill a PhD thesis are feeling at ease in an environment of scientific dynamics and wanting to learn, listen, share, and work in the unknown. There is no clear and definite answer, and often no clear-cut notion of “right” or “wrong” until the scientific community has weighed in. Expect long, probing discussions with your advisor, lab-mates, conference audiences, reviewers, and peers who may challenge or disagree with you. Debate is part of the process.
Candidates must have a Master’s degree (or equivalent) in Computer Engineering or related areas relevant to the PhD topic
Inria est l’institut national de recherche dédié aux sciences et technologies du numérique. Il emploie 2600 personnes. Ses 215 équipes-projets agiles, en général communes avec des partenaires académiques, impliquent plus de 3900 scientifiques pour relever les défis du numérique, souvent à l’interface d’autres disciplines. L’institut fait appel à de nombreux talents dans plus d’une quarantaine de métiers différents. 900 personnels d’appui à la recherche et à l’innovation contribuent à faire émerger et grandir des projets scientifiques ou entrepreneuriaux qui impactent le monde. Inria travaille avec de nombreuses entreprises et a accompagné la création de plus de 200 start-up. L'institut s'efforce ainsi de répondre aux enjeux de la transformation numérique de la science, de la société et de l'économie.
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