智能传感与片上学习硅生命周期方向博士研究员（科研助理，TVL-E13/100 %）
Open Ph.D. Position (TVL-E13/100 %) as part of the industry-sponsored Graduate School Intelligent Methods for Test and Reliability (GS-IMTR) at the University of Stuttgart
原帖优先：申请材料、截止时间与资格以原帖和学校官方说明为准。
AI 中文速览
- 研究内容
- 候选人将作为斯图加特大学智能传感器研究所 GS-IMTR 研究生院 P14 项目“硅生命周期的智能传感与片上学习”的一部分开展研究。项目探索硅生命周期管理带来的芯片设计挑战与测试机遇，重点关注数字片上传感器与边缘AI相结合的高效数据收集与处理，以及片上在线学习，并开发用于最先进数据转换器的测试程序。
- 申请条件
- 要求持有电气工程、计算机科学、物理学或相关学科的硕士学位（或同等学历）。应聘者应具备机器学习和FPGA编程的强大背景，熟悉数模混合集成电路设计，具备微电子学或类似领域的扎实基础，具有团队合作能力、灵活性与奉献精神，并具备非常好的英语知识。
- 待遇
- 提供为期 3 年、TVL-E13/100% 的全职博士岗位，起薪根据经验水平每年总毛收入超过 45,000 欧元。提供与 Advantest 公司的紧密合作、刺激的研究环境、最先进的 IC 设计工具与混合信号实验室，以及从德国领先技术大学获得博士学位的可能性。
- 申请方式
- 通过 Stelwerk 招聘平台或斯图加特大学研究所网站提供的链接进行申请，或联系 Prof. Dr. Jens Anders。
- 材料清单
- 动机信
- 简历
- 证书
- 成绩单
由 gemini-2.5-flash-lite 生成，博士岗判定置信度 100%。
岗位信息
- 截止
- （Europe/Berlin） 剩 349 天
- 学科
- 计算机科学
- 合同类型
- 雇佣合同
- 薪资制度
- 德国各州公共服务集体工资协议（TV-L） · E 13
- 原帖薪资说明
- TVL-E13
- 原文薪资
- EUR 45,000 / 年（税前）
- 本站收录
- 内容更新
- 原帖导师候选（待核验）
- Prof. Dr. Jens Anders
- 来源
- DAAD PhDGermany 博士岗位与项目 · 最近核对 2026-10-15
- 详情核验
薪资与生活预算（估算）
- 税前月薪
- 约 EUR 3,750 / 月
- 税后月薪（情景估算）
- 约 EUR 2,475 / 月 ≈ ¥19,553 / 月
按税前扣除 34% 试算，包含所得税与雇员社保的简化预算；不代表个人实际税率。
- 月租预算
- EUR 550 / 月（比较情景，非所在城市或德国平均租金）
- 扣房租后（估算）
- 约 ¥15,208 / 月
仅减房租，尚未扣除食品、交通、水电等其他生活费。
计算依据与调整预算
单身、无子女、无教会税的比较情景；34%为本站假设，不是税级I的固定税率或完整德国工资税计算。实际扣除取决于税级、医保、社保及补充养老等。 德国财政部工资税计算器 ↗只计算相关税额，社保等需另计。
税后 = 税前 ×（1 − 扣除比例）；人民币 = 税后欧元 × 汇率；房租后 =（税后欧元 − 房租）× 汇率。汇率 7.9 为情景输入，未核验为实时牌价，房租 550 欧元为预算假设。
参数只在当前页面试算，不上传服务器，不改变原帖数据。
判定依据（原文摘录）
- 这是一项博士培养机会
Open Ph.D. Position (TVL-E13/100 %) as part of the industry-sponsored Graduate School Intelligent Methods for Test and Reliability (GS-IMTR) at the University of Stuttgart
- 要求硕士学位而非仅学士
We are looking for candidates holding a Master’s degree (or equivalent) in electrical engineering, computer science, physics, or related subjects
- 工作语言包含德语和英语
Working Language German, English
原文
Back to Overview
Open Ph.D. Position (TVL-E13/100 %) as part of the industry-sponsored Graduate School Intelligent Methods for Test and Reliability (GS-IMTR) at the University of Stuttgart Full PhD Working Language German, English
Location Stuttgart
Application Deadline 30. Sep 2027
Starting Date as soon as possible
• Overview • Description • Required Documents • Application
Overview Open Positions 1
Time Span as soon as possible for 3 years
Application Deadline 30. Sep 2027
Financing yes
Type of Position Full PhD
Working Language • German • English
Required Degree Master
Areas of study Applied Computer Science, Computer Engineering, Computer Science, Theoretical Computer Science, Information Technology, Electrical Engineering
Description Description GS-IMTR, which is a joint endeavor between the University of Stuttgart and Advantest, an industry leader in automatic test equipment, focuses on topics such as design for test and diagnosis; post-silicon validation; test generation and optimization; robust device tuning; system-level test; lifetime test and reliability management; and test automation. Further information can be found under https://www.gs-imtr.uni-stuttgart.de/ .
The position to be filled is located at the Institute of Smart Sensors at the University of Stuttgart ( https://www.iis.uni-stuttgart.de/ ). We are looking for candidates holding a Master’s degree (or equivalent) in electrical engineering, computer science, physics, or related subjects interested in pursuing research as part of GS-IMTR’s project P14: Intelligent Sensing and On-Chip Learning for Silicon Lifecyle.
Here, project P14 explores the challenges that silicon lifecycle management introduces into the chip design process and, more importantly, the opportunities that it brings to the area of test. In particular, we will focus on the possibilities associated with digital on-chip sensors combined with edge AI in the tester to collect and process the data very efficiently at run-time. Further, we will also investigate the possibility of on-chip online learning on the collected data. The project also involves the developing of a test program for a state-of-the-art data converter, including the collection and processing of statistically relevant data.
The candidates should have a strong background in machine-learning and FPGA programming and be familiar with mixed-signal integrated circuit design.
What we offer: • The possibility to conduct cutting-edge research as part of GS-IMTR • Strong interactions with the company Advantest throughout the project • A stimulating research environment with more than 20 Ph.D. students working on a broad range of IC design topics for various applications in smart sensing for biomedical and materials science applications as well as quantum technologies • The possibility of obtaining a Ph.D. degree from one of Germany’s leading technical universities • Access to all state-of-the-art IC design tools • Large experience in IC manufacturing • A fully equipped mixed-signal lab for chip characterizations • Access to state-of-the-art cleanroom manufacturing technologies via a strong collaboration with IMS CHIPS in Stuttgart • Collaborations with leading industrial and academic partners • Competitive annual gross salary – depending on experience level – of >45.000€
What we expect : • The ability to work in a team • Flexibility and dedication • Strong motivation to introduce innovations into a current research topic • Experience in machine learning • Experience in FPGA programming • Experience in analog and mixed-signal integrated circuit design • Strong background in microelectronics or a similar field of study • Curiosity to expand your knowledge into interesting applications • Very good knowledge of the English language
Required Documents Required Documents • Motivation letter • CV • Certificates • Transcripts
Application Application
https://www.stellenwerk.de/stuttgart/jobboerse/open-phd-position-at-the-institute-of-smart-sensors-in-smart-ic-testing-as-part-of-the-graduate-schol-gs-imtr-240724-190950/
https://www.iis.uni-stuttgart.de/de/institut Contact Universität Stuttgart Institut für Intelligente Sensorik und Theoretische Elektrotechnik Prof. Dr. Jens Anders Address Street Pfaffenwaldring 47 Zipcode 70569 City Stuttgart
Contact details Tel: +49 71168567250 E-Mail: jens. anders at iis. uni-stuttgart. de Web: https://www.iis.uni-stuttgart.de/de/institut