Research Associate & PhD Student for DFG-funded project “Process Mining from Multimodal Data for Anomaly Detection in Manual Work”
Klu Ham
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Education & alternatives
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 We offer
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- Python
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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 We offer
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- Oct 18, 2026 · today
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Job description
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.
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
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.
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Klu Ham
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