计算机与信息研究科学家
AI 替代率
70%这个岗位当前已结合 10 条时间线资讯和岗位画像推理来给出替代率。
计算机与信息研究科学家的角色面临较高的AI替代风险，这主要是因为AI在自动化和增强核心研究、开发和分析任务方面的能力日益增强，众多专门为研究人员设计的最新进展和工具证明了这一点。
替代率趋势
按周期刷新快照聚合- 2026-04-2055%
为什么是这个等级
结构底座Many aspects of computer and information research, such as data analysis, running simulations, and model experimentation, involve repetitive and rule-based tasks that are highly amenable to AI-driven automation.
The role inherently deals with information, algorithms, and computational models, making it particularly susceptible to AI-driven transformation in how research is conducted, accelerated, and even conceptualized.
Recent official reports from leading AI labs indicate AI's growing ability to perform core research tasks, including contributing to breakthroughs in mathematics and theoretical computer science, signifying a direct impact on the domain of research scientists.
Platforms are actively rolling out advanced AI models, inference capabilities, and AI coding agents specifically tailored to assist and accelerate academic and scientific researchers, streamlining their workflows and automating key development tasks.
New capabilities, such as those for deploying local AI agents and strengthening model testing/evaluation with AI, demonstrate that even complex development and validation processes are becoming increasingly automated or heavily assisted by AI.
时间线
按时间倒序展示相关资讯与案例首个AI软件工程师上线，已通过公司面试并有望取代程序员工作。这标志着AI技术在软件工程领域的一个重大能力更新，由一支技术卓越的华人创始团队主导研发。
打开原文清华大学教授、智源研究院副院长唐杰认为，认知智能将成为未来十年人工智能发展的重要方向。
打开原文AI 与生物物理建模结合，提升蛋白质设计效率 德国莱比锡大学研究团队在Rosetta框架内开发了机器学习工具，用于预测氨基酸概率，并测试了其在蛋白质设计中的表现。 研究发现，ML方法在清除有害突变方面优于传统方法，但评分和排序仍是挑战。
打开原文由于 Gemini 暂时不可用，该来源被挂到最接近的岗位上，以便先出现在岗位时间线中。
打开原文腾讯为大模型人才制定了前所未有的标准，文章重点关注“AI for Science”和“生物大模型”研究，并提及顶级AI会议，这预示着高级AI研究职位的招聘方向和人才需求发生了显著转变。
打开原文Liquid AI introduces LFM2.5-2.6B, a compact, open-weight language model optimized for agentic workloads on local hardware like Raspberry Pi, without needing cloud or GPUs. This model supports on-device AI for privacy-sensitive and connectivity-limited environments, emphasizing tool-calling and workflow automation. It offers a base for fine-tuning, supports major inference stacks for deployment across consumer to embedded systems, and leverages unique training methods for agents rather than chatbots. This capability update provides new options for developers and enterprises in edge AI, impacting research and development in model efficiency and local deployment strategies.
打开原文Hugging Face announces Baseten as a new inference provider, expanding capabilities for deploying and running AI models for developers and researchers.
打开原文Meta has launched Muse Code, an AI agent aimed at assisting with complex coding tasks in large software projects, enhancing capabilities for those working with extensive codebases.
打开原文OpenAI announces new safeguards and practices for third-party cybersecurity evaluations of its AI models, strengthening model testing and evaluation processes.
打开原文Hugging Face introduces a new capability for deploying local AI agents using LFM2.5-2.6B, enhancing the tools available for computer and information research scientists working with AI model and agent development.
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