AI技术助理研究员（博士实习）AI Technical Assistant Researcher(PhD Intern)

岗位职责/Job Description： 1\.负责人工智能核心技术研究与开发，包括机器学习算法设计、深度学习模型优化、大模型训练与部署，以及AI系统架构设计； 2\.探索AI技术在垂直领域（如5/6G，web3\.0，教育，医疗，法律，金融，AI4Science等）的应用场景，设计端到端解决方案并推动落地验证； 3\.主导AI平台与工具的研发，涵盖数据治理、模型训练、推理加速、自动化评估等全链路技术攻关； 4\.开展跨团队协作，推进产学研合作、开源社区贡献、学术论文发表及专利布局； 5\.完成领导交办的其他任务。 1\.Lead research and development of core AI technologies, including machine learning algorithm design, deep learning model optimization, large language model training and deployment, and AI system architecture design. 2\.Explore AI application scenarios in vertical domains (e.g., 5/6G, Web3\.0, education, healthcare, legal, finance, AI4Science), design end-to-end solutions, and drive implementation validation. 3\.Spearhead development of AI platforms and tools, covering full-chain technical challenges including data governance, model training, inference acceleration, and automated evaluation. 4\.Facilitate cross-team collaboration, promote industry-academia cooperation, open-source community contributions, academic paper publications, and patent portfolio development. 5\.Complete other tasks assigned by the leadership. 岗位要求/Job Responsibility： 1\.全日制在读博士，计算机科学、数学、统计学、人工智能、数据科学等专业优先；具有开源社区贡献经验者优先； 2\.具备扎实的机器学习、深度学习理论基础，熟悉主流算法模型（如CNN/RNN/Transformer/GAN等），有计算机视觉（CV）、自然语言处理（NLP）、大模型，强化学习等领域研发经验者优先； 3\.熟练使用TensorFlow/PyTorch等框架，掌握Python/C\+\+等编程语言，具备分布式训练、模型压缩、边缘端推理等工程化经验；具有大模型（如LLM、多模态模型）开发经验者优先； 4\.具备AI与垂直领域（如5/6G，web3\.0，教育，医疗，法律，金融，AI4Science）结合的实践经验者优先； 5\.具备优秀的沟通和协调能力，具备流利的英语听说读写能力，可使用英文开展日常科研工作。 1\.PhD candidate in Computer Science, Mathematics, Statistics, Artificial Intelligence, or Data Science. Open-source community contributors is a plus. 2\.Strong theoretical foundation in machine learning and deep learning, familiar with mainstream algorithms (CNN/RNN/Transformer/GAN). R\&D experience in computer vision (CV), natural language processing (NLP), large language models, or reinforcement learning. 3\.Proficient in TensorFlow/PyTorch frameworks and Python/C\+\+ programming languages. Engineering experience in distributed training, model compression, and edge-side inference required. Large language model development experience (including MMLLM) is a plus. 4\.Practical experience in integrating AI with vertical domains (5/6G, Web3\.0, education, healthcare, legal, finance, AI4Science). 5\.Excellent communication and coordination skills with fluent English proficiency (written and spoken) for daily research activities.