自动驾驶与公共交通方向博士职位
Doctoral Researcher (TV-L E13) - "Autonomous Driving in Public Transport"
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
- 研究自动驾驶出行服务对出行行为的影响，支持公共交通系统中自动驾驶实施的技术、运营和社会基础建设。
- 申请条件
- 需相关领域的硕士学位或同等学历，对交通建模、规划或出行研究感兴趣，掌握经验调查方法和选择建模，具备Java或MATSim编程经验者优先，英语优秀且具备德语工作知识。
- 待遇
- 提供国际化和协作性的研究环境、灵活的工作条件，以及根据TV-L E13标准的竞争性薪酬。
- 申请方式
- 请将申请材料合并为一个PDF文件发送至指定邮箱，滚动录取直至岗位填满。
- 材料清单
- 求职信（最多两页）
- 个人简历
- 三位推荐人的姓名及联系方式
由 gemini-2.5-flash-lite 生成，博士岗判定置信度 100%。
结构化信息
- 截止
- 原帖未给出
- 学科
- 工程
- 合同类型
- 雇佣合同
- 本站收录
- 内容更新
- 来源
- Technische Universität München 官方招聘 · 最近核对 2026-10-07
判定依据（原文摘录）
- is_phd
Doctoral Researcher (TV-L E13) - "Autonomous Driving in Public Transport"
- english_ok
Excellent written and spoken English skills and working knowledge of German.
- bachelor_ok
Master's degree or equivalent qualification in a relevant field.
原文
Doctoral Researcher (TV-L E13) - "Autonomous Driving in Public Transport"
11.08.2026, Academic staff
The Professorship for Travel Behavior at the Department of Mobility Systems Engineering, Technical University of Munich (TUM), is seeking a Doctoral Researcher (TV-L E13) to join a three-year research project on the future of autonomous driving in public transport, expected to start on October 1, 2026 (subject to funding approval).
The position focuses on understanding the effects of autonomous mobility services on travel behavior and supporting the development of technological, operational, and societal foundations for the implementation of autonomous public transport systems.
Your Responsibilities • Design and conduct empirical surveys, including stated-preference and revealed-preference studies, to investigate user preferences and behavioral responses to autonomous mobility services. • Develop and estimate discrete choice models for transportation mode choice decisions. • Implement and apply agent-based transport simulations to assess demand and modal-split changes under different policy and technology scenarios. • Collaborate with project partners to integrate behavioral findings into system-level impact assessments. • Contribute to project reports, scientific publications, conference presentations, and stakeholder engagement activities. • Participate in teaching activities within TUM's M.Sc. Transportation Systems program.
Your Profile • Master's degree or equivalent qualification in a relevant field. • Strong interest in transport modeling, transport planning, mobility, or related research areas. • Knowledge of empirical survey methods and choice modeling. • Programming experience is desirable, particularly with Java and/or MATSim. • Excellent written and spoken English skills and working knowledge of German.
We Offer An international and collaborative research environment, flexible working conditions, and competitive remuneration according to TV-L E13. The position provides excellent opportunities for scientific publication, conference participation, and academic development within a leading research university.
Applicants should submit a letter of interest (maximum two pages), a curriculum vitae, and the names and contact details of three references as a single PDF file to applications.tb@ed.tum.de . Applications will be reviewed on a rolling basis until the position is filled.
The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.
Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.
Kontakt: qin.zhang@tum.de
More Information
https://www.mos.ed.tum.de/en/tb/open-positions/