Research Assistant/Associate - Postdocs
The Process and Data Science (PADS) group, headed by Prof. Dr. Ir. Wil van der Aalst, is a new research group at RWTH focusing on the interplay between processes and data. PADS symbolizes RWTH’s ambitions in the area of Data Science and is supported through a recently awarded Alexander von Humboldt Professorship (Germany’s most valuable international research award with value of 5 million euros). The scope of PADS includes all topics where discrete processes are analyzed, reengineered, and/or supported in a data-driven manner. Process-centricity is combined with an array of Data Science techniques (machine learning, data mining, visualization, and Big data infrastructures). The main focus is on Process Mining (including process discovery, conformance checking, performance analysis, predictive analytics, operational support, and process improvement). This is combined with neighboring disciplines such as operations research, algorithms, discrete event simulation, business process management, and workflow automation. The chair of PADS is the founder of the process mining discipline and one of the leading computer scientists in the world. The ambition is to realize scientific breakthroughs which will help organizations to turn event data into business and societal value. Investments by RWTH, the Alexander von Humboldt foundation, and the Fraunhofer Institute for Applied Information Technology make it possible to realize these ambitions and to provide unique opportunities for ambitious Postdocs.
- Applicants must have a doctorate/Ph.D. or equivalent.
- You have a doctorate/PhD in computer science or a related discipline (e.g., statistics, operations research or management science with a specialization in data and/or process science).
- You have proven to be an independent and strong researcher (supported by a good publication track record).
- You are a fast learner, dedicated, autonomous and creative.
- You have a genuine interest (or experience) in process mining and are willing to demonstrate this as part of the application process.
- You have excellent analytical skills and you are willing to implement your ideas in software together with PhDs and Master students.
- You are ambitious, but at the same time a team player.
- You are eager and able to (co-)supervise PhD students and take a leading role in research projects.
- You have excellent communicative skills (also in English).
- You will do cutting-edge process mining research in one of the top groups in data science.
- You will take a leading role in research projects with industrial partners that provide data and give feedback on research results.
- You will supervise PhD, Bachelor and Master students working on related topics and have a limited involvement in teaching.
- You will present your work at national and international conferences and publish in the leading journals in your discipline.
Within the Process and Data Science (PADS) group there are four smaller subgroups working on (1) foundations of process mining, (2) dealing with large/distributed/streaming/uncertain event data, (3) automated operational process improvement, and (4) responsible process mining (focusing on challenges related to fairness, accuracy, confidentiality, and transparency). The postdocs are expected to take an important role in these subgroups and co-supervise PhDs working in these group.
What we offer
The position is for 4 years (full-time). The initial appointment is for one year, followed by an extension of 3 or more years.
The salary corresponds to level EG 13 TV-L.
RWTH Aachen University is certified as a “Family-Friendly University”. We particularly welcome and encourage applications from women, disabled persons and ethnic minority groups, recognizing they are underrepresented across RWTH Aachen University. The principles of fair and open competition apply and appointments will be made on merit.
Your contact person
For further details, please contact
Tel.: +49 (0) 241 80 21902
Please send your application to
Informatik 9 – PADS
Prof. Dr. Wil van der Aalst