博士研究生岗位 F/M：在机器人生成式世界模型中强化持久性

该博士项目致力于开发用于机器人技术的生成式世界模型中的持久性机制，重点研究在图像生成过程中整合物理概念的算法。研究工作包括将持久性概念形式化以及实施轨迹级学习方法，要求参与者需参加各类科学会议与研讨活动。具备 Python、人工智能工具及计算机视觉方面的技能者优先。

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 (**). * ［会员资料链接］ ** ［会员资料链接］ 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). 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.

福利包： 补贴餐食 部分公共交通费用报销 休假规定：每年7周年假 + 因RTT（法定工作时间减少）额外享有10天假期 + 可能享受特殊假期（如照顾生病的子女、搬家等）。 远程工作可能性（在任职6个月后）及灵活的工作时间安排 提供专业设备（视频会议、计算机设备借用等） 社会、文化和体育活动及项目 职业培训机会 社会保障覆盖范围 申请该职位

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.