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PhD Position F/M Enforcing Persistence in Generative World Models for Robotics

Inria (French Institute for Research in Computer Science and Automation)

Posted Oct 22, 2026
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Skills named in this posting

  • Python
  • PyTorch / TensorFlow
PhD Position F/M Enforcing Persistence in Generative World Models for Robotics Download job offer in PDF format Contract type : Fixed-term contract Level of qualifications required : Graduate degree or equivalent Fonction : PhD Position Level of experience : Recently graduated Context AI4IDF is a structuring and unifying research project dedicated to artificial intelligence, a scientific and technological field that has become essential. Aiming to deepen knowledge in AI while keeping human beings at the center of its concerns, the Ile-de-France Region aspires to play a major role in this promising sector, through its scientific excellence and its incomparable ecosystem, and wishes to make the latter a key player in building a frugal, reliable, and efficient Artificial Intelligence (AI), designed to coexist with humans and assist them in their decisions. To this end, DIM AI4IDF periodically launches calls for doctoral research projects. This thesis falls within this framework and establishes a partnership between the Hi!Paris and PRAIRIE clusters, specifically between Telecom ParisTech and Inria Paris Centre. The objective of this thesis is to conduct joint research on persistence in generative world models for robotics and to develop algorithms capable of integrating physical concepts during image generation in particular. The project will develop methods to enforce persistence in generative world models, with contributions including a formal definition of persistence, trajectory-level learning methods, and empirical validation in robotic prediction and control. Regular travel is expected for this position, notably for dissemination purposes, scientific training, and participation in project and collaboration meetings. Assignment Responsibilities: Under the guidance of researchers from Inria and Telecom ParisTech, the successful PhD candidate will carry out scientific research and software development under the direct supervision of their supervisors. For further information on the proposed research topic: A state-of-the-art review, a bibliography and scientific references are available at the following URL; please feel free to visit the site: Collaboration: The successful candidate will be linked to the research and training ecosystems of Telecom ParisTech and the Paris centre of Inria. In particular, the Multimedia (MM) laboratory at Telecom ParisTech (*) and the ASTRA project team at Inria Paris (**). * https://www.telecom-paris.fr/en/research/labs/information-processing-ltci/teams/multimedia ** https://astra-team.github.io Main activities Main activities: • Conducting research and development • Writing scientific articles and reports • Contribute to the dissemination and popularisation of scientific knowledge • Undertake scientific and professional development training • Participate in the activities of their research teams and in events organised by their laboratories Other activities: • Participate in contractual activities and collaborative projects undertaken by their respective teams. Skills Technical skills and level required: Languages: proficiency in English (written and spoken) is required. French is strongly recommended. Interpersonal skills: being open to multicultural and inclusive research environments and adhering to the social and professional code of conduct established in the host laboratories. Respecting professional and conduct rules as well as research ethics is required. Additional skills appreciated: proficiency in tools, languages, and development libraries for computer vision and AI development. The essential combination is Python, PyTorch, Git (Linux is a plus), complemented by skills in GPU computing, large-scale data processing, and a solid mathematical background. Specifically for the subject of this thesis, knowledge in the following areas is strongly recommended: Generative models: diffusion (Stable Diffusion, DDPM), flows, VAE. Frugal AI: quantization, pruning, distillation, edge computing (TensorRT, ONNX). 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 Apply for this position Share • Facebook • Linkedin • Twitter • Email General Information • Theme/Domain : Robotics and Smart environments Statistics (Big data) (BAP E) • Town/city : Paris • Inria Center : Centre Inria de Paris • Starting date : 2026-11-01 • 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 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 : ASTRA • PhD Supervisor : Nashashibi Fawzi / Fawzi.Nashashibi@inria.fr The keys to success The doctoral candidate sought must be motivated for long-term scientific research and feel comfortable in a dynamic, multicultural scientific environment. A love of learning and listening are essential qualities for succeeding in this mission. Passionate about research and innovation, they must be able to interact with both academic and industrial partners. They must have skills and a particular taste for developing artificial intelligence architectures and methods. Expertise in computer programming is required, as well as in scientific writing in English. 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.

RISC-V ecosystem

Inria (French Institute for Research in Computer Science and Automation) in the RISC-V ecosystem

RISC-V International: Community

The French Institute for Research in Computer Science and Automation (French: Institut national de recherche en informatique et en automatique) is a French national research institution focusing on computer science and applied mathematics.

  • RISC-V security research: mentorship projects implementing RISC-V ISA extensions for control-flow and data-flow integrity
  • Microarchitecture-security research relevant to RISC-V CPUs

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