DFG资助项目“多模态数据流程挖掘异常检测”科研助理兼博士研究员
Research Associate & PhD Student for DFG-funded project “Process Mining from Multimodal Data for Anomaly Detection in Manual Work”
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
- 在DFG资助的项目“Process Mining from Multimodal Data for Anomaly Detection in Manual Work”中开展流程挖掘、人工智能和数据分析领域的独立研究,开发、实现和评估新方法与工具,并以完成博士学位为目标。
- 申请条件
- 持有计算机科学、数据科学、信息系统、工业工程或相关领域的优秀硕士学位(或同等学历);具备扎实的编程技能(如Python)以及机器学习或数据分析的坚实基础;英语口语和书写能力优秀,无需德语。
- 待遇
- 提供薪资基于TV-L E13(视资质而定);接受流程挖掘领域国际知名研究人员的指导,并与学术界和工业界伙伴紧密合作;提供参加国际会议的差旅资助;工作地点位于汉堡,提供充满活力、国际化的工作环境。岗位期限为36个月。
- 申请方式
- 请将完整的申请文件通过电子邮件发送至 klu-jobs@m.personio.de 或通过申请按钮提交。滚动录取,收到申请即开始评估,建议立即申请。
- 材料清单
- 包含愿意担任导师的常驻教职员工姓名的求职信
- 研究陈述
- 视频陈述(最长3分钟)
- 完整简历(CV)
- 两封推荐信(含完整联系方式)
- 英语能力证明(若先前学位的官方语言不是英语)
- 学士学位证书及完整成绩单
- 硕士学位证书及完整成绩单
- 学位补充件(若可用)
- 大学评分系统说明(德国境外获得的学位必需)
- 所有非英语或德语学位文件及成绩单的官方翻译件
- 个人卓越表现的质量指标(如奖项、奖学金)、项目卓越表现(如班级排名、论文成绩/排名)以及大学排名信息
由 gemini-2.5-flash-lite 生成,博士岗判定置信度 100%。
岗位信息
- 截止
- 原帖未给出
- 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;具体金额请核对原帖及适用工资表
- 原帖薪资说明
- TV-L E13
- 原帖发布
- 本站收录
- 内容更新
- 原帖导师候选(待核验)
- Henrik Leopold
- 来源
- Kühne Logistics University - Wissenschaftliche Hochschule für Logistik und Unternehmensführung 官方招聘(待采集验收) · 最近核对 2026-10-20
- 详情核验
判定依据(原文摘录)
- english_ok
Excellent command of English; German is not required
原文
We are seeking for The Kühne Logistics University (KLU) invites applications for a doctoral researcher in the DFG-funded project “Process Mining from Multimodal Data for Anomaly Detection in Manual Work”, led by Prof. Dr. Henrik Leopold in cooperation with TU Wien. The project looks at how process mining can go beyond traditional event logs by using richer data sources, such as video, audio and sensor data, to better understand and improve how work is actually done. The position is limited to 36 months.
Your Responsibilities • Carry out independent research on process mining, AI and data analytics, with the goal of completing a doctoral degree • Develop, implement and evaluate new methods and tools, for example for event log extraction, process discovery, conformance checking or anomaly detection • Apply machine learning methods (e.g. computer vision, NLP, foundation models) to process-related data • Publish and present results at international conferences and in journals • Work with the project partners at TU Wien and with industry partners • Contribute a modest share of support to teaching and to the department’s academic activities
Your qualifications • Very good Master’s degree (or equivalent) in computer science, data science, information systems, industrial engineering or a related field • Strong programming skills (e.g. Python) and solid knowledge of machine learning or data analytics • Interest in business processes and in research that brings together AI and organizational practice • Prior experience with process mining, computer vision or NLP is a plus but not required • Excellent command of English; German is not required • Curiosity, a structured way of working and enjoyment of working in an international team
Admission and Eligibility Admission to the program is competitive and based on the applicant’s excellence as well as the match in research interest. We encourage you to apply immediately, since the reviews of applicants and the selection start upon receipt of applications. Evaluation of the applications is done on a rolling basis as they are submitted. • To be considered for admission, applicants must meet these minimum requirements: • Completed or about to complete a Master’s degree or equivalent (300 ECTS) from an accredited university with a good international reputation with the German grade 2.0 or better. Grade equivalents are required for international applicants. • English language proficiency according to KLU requirements (if the official language of the previous degree wasn’t English)
Full details about the application procedure can be found here. You should submit: • Cover letter (incl. name of the member of the resident faculty who is willing to act as your supervisor). • Research statement. • Video statement (max. 3 minutes). • A full resume (CV). • Two references (with full contact details). • Evidence of your English proficiency according to KLU requirements (if the official language of the previous degree wasn’t English). • Bachelor’s degree certificate and full transcript of records • Master’s degree certificate and full transcript of records • Diploma Supplements (if available) • University grading system information (required for degrees obtained outside • Germany) • Official translations of all degree documents and transcripts of records not issued in English or German • Quality indicators for your individual excellence (e.g., prizes, scholarships), • Excellence in your program (e.g., class rank, thesis grade/rank), and your university(e.g., university rankings)
PhD KLU supports the scientific employee in writing a dissertation on the research topic. As a state-recognized university, KLU has the right to award doctoral degrees. The dissertation is usually done cumulatively on the basis of three scientific papers.
We offer • Salary based on TV-L E13, depending on qualifications • Supervision by an internationally recognized researcher in process mining, with close links to academic and industry partners • Funding for conference travel and the chance to join an international research community • A dynamic, international work environment in Hamburg
We value diversity We value diversity and therefore welcome all applications regardless of gender, nationality, ethnic and social origin, religion and worldview, disability, age, sexual orientation, and identity.
Contact Please send your complete application documents by email to klu-jobs@m.personio.de or via the Apply button.