长鑫存储DRAM新型产品测试预研(J17327)
校招全职电路设计类地点:合肥 | 上海状态:招聘
任职要求
学历要求:硕士及以上,博士优先 专业要求:微电子、电子工程、计算机科学、物理学、统计学等相关专业 其他要求: 1.专业背景: -精通DRAM测试全流程(CP、FT、WAT),熟悉高速接口测试(如眼图、抖动分析)、可靠性测试(HTOL、ESD)及多物理场耦合分析 -具备AI在测试领域的研究经验,研究方向包括:强化学习优化测试序列、生成式对抗网络(GAN)模拟极端测试场景等 2.工具与技能: -熟练使用Python、Matlab进行测试数据分析与建模,掌握V93000、Ultraflex测试机台编程能力。 -熟悉大数据处理技术(如Spark、Flink)及分布式测试系统架构者优先 3.项目经验: -参与过DRAM测试方案开发,或主导过超高速接口硅后验证项目 -在ITC、IEEETestConference等顶级会议发表过测试相关论文者优先 4.综合素质: 具备将测试需求转化为统计模型的能力,对测试数据异常模式有敏锐洞察力 适应高强度技术攻关,能在6个月内完成从算法设计到量产测试方案的落地闭环 优秀的跨团队协作能力,可同步对接设计、工艺及可靠性团队
工作职责
1.前瞻性测试系统开发: -构建面向未来DRAM产品的智能测试平台,攻克超高速接口测试、3D堆叠结构(TSV)多物理场耦合分析等难题。 -研发AI驱动的动态测试策略引擎,实现测试用例自动化生成与覆盖率实时优化,测试效率提升。 2.缺陷预测与根因溯源: -开发基于深度学习的缺陷预测模型,提前识别潜在失效模式。 -构建多维度测试数据湖,融合电性参数、工艺波动与可靠性数据,实现缺陷根因的毫秒级定位。 3.测试流程创新: -主导AI与传统测试设备的深度集成,推动测试向量自主优化与自适应校准。 -开发面向存算一体(PIM)架构的功能-性能联合测试框架,突破近存计算场景下的验证瓶颈。 4.跨领域协同与标准制定: -联动设计团队建立测试约束左移机制,在架构设计阶段介入风险验证。 -参与JEDEC/IEEE测试标准制定,主导超低电压(VLP)测试方法论与车规级DRAM(AEC-Q100)可靠性验证规范提案。
包括英文材料
学历+
强化学习+
https://cloud.google.com/discover/what-is-reinforcement-learning?hl=en
Reinforcement learning (RL) is a type of machine learning where an "agent" learns optimal behavior through interaction with its environment.
https://huggingface.co/learn/deep-rl-course/unit0/introduction
This course will teach you about Deep Reinforcement Learning from beginner to expert. It’s completely free and open-source!
https://www.kaggle.com/learn/intro-to-game-ai-and-reinforcement-learning
Build your own video game bots, using classic and cutting-edge algorithms.
Python+
https://liaoxuefeng.com/books/python/introduction/index.html
中文,免费,零起点,完整示例,基于最新的Python 3版本。
https://www.learnpython.org/
a free interactive Python tutorial for people who want to learn Python, fast.
https://www.youtube.com/watch?v=K5KVEU3aaeQ
Master Python from scratch 🚀 No fluff—just clear, practical coding skills to kickstart your journey!
https://www.youtube.com/watch?v=rfscVS0vtbw
This course will give you a full introduction into all of the core concepts in python.
MATLAB+
https://matlabacademy.mathworks.com/?page=1&sort=featured
Learn MATLAB and Simulink through interactive, in-product exercises
https://www.mathworks.com/help/matlab/getting-started-with-matlab.html
Millions of engineers and scientists worldwide use MATLAB® to analyze and design the systems and products transforming our world.
https://www.youtube.com/watch?v=7f50sQYjNRA
Learn the fundametnals of MATLAB in this tutorial for engineers, scientists, and students.
数据分析+
[英文] Data Analyst Roadmap
https://roadmap.sh/data-analyst
Step by step guide to becoming an Data Analyst in 2025
Spark+
[英文] Learning Spark Book
https://pages.databricks.com/rs/094-YMS-629/images/LearningSpark2.0.pdf
This new edition has been updated to reflect Apache Spark’s evolution through Spark 2.x and Spark 3.0, including its expanded ecosystem of built-in and external data sources, machine learning, and streaming technologies with which Spark is tightly integrated.
Flink+
https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/learn-flink/overview/
This training presents an introduction to Apache Flink that includes just enough to get you started writing scalable streaming ETL, analytics, and event-driven applications, while leaving out a lot of (ultimately important) details.
https://www.youtube.com/watch?v=WajYe9iA2Uk&list=PLa7VYi0yPIH2GTo3vRtX8w9tgNTTyYSux
Today’s businesses are increasingly software-defined, and their business processes are being automated. Whether it’s orders and shipments, or downloads and clicks, business events can always be streamed. Flink can be used to manipulate, process, and react to these streaming events as they occur.
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
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