“人工智能 + 物理学”人才培养模式构建及实践

Construction and Practice of the “AI + Physics” Talent Training Model

摘要: 在人工智能高速发展的背景下，社会对人才素质提出了更高要求，这也迫使高校人才培养模式做出改变。为提高物理专业人才的综合能力，高校应将人工智能融入物理人才培养体系，从而培养出高素质复合型人才。构建物理学 + 人工智能的跨学科课程体系，加强学生对多学科知识的掌握。组建多学科指导团队，鼓励学生参与研究项目，强化科研训练和实践教学，提高学生解决复杂问题的能力。推进产学研合作，企业深度参与课程设置、师资配备、教学实训、毕业考核全流程，实现人才培养与产业链需求无缝对接。通过发展“人工智能 + 物理学”模式，培养出一批物理基础扎实、人工智能技术熟练的、企业真正需要的高水平人才，最终形成一个可复制、可扩展的跨学科人才培养模式。

Abstract: Against the backdrop of rapid advancements in artificial intelligence, society has set higher standards for talent quality, compelling universities to transform their talent cultivation models. To enhance the comprehensive capabilities of physics professionals, universities should integrate artificial intelligence into the physics talent cultivation system, thereby developing high-quality interdisciplinary talents. This involves building a cross-disciplinary curriculum of “Physics + AI” to strengthen students’ command of multidisciplinary knowledge, assembling multidisciplinary advisory teams, encouraging student participation in research projects, reinforcing research training and practical teaching, and improving students’ ability to solve complex problems. Industry-academia-research collaboration should be advanced, with enterprises deeply involved in the entire process of curriculum design, faculty staffing, practical training, and graduation assessment, achieving seamless alignment between talent cultivation and industrial chain demands. By developing the “AI + Physics” model, a cohort of high-level talents with solid physics foundations, proficient AI skills, and genuine enterprise demand can be cultivated, ultimately forming a replicable and scalable interdisciplinary talent cultivation model.