Research Assistant/Associate - Postgraduates
The Process and Data Science group, headed by Prof. 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 a talented student do PhD research in process mining.
- You have an University degree (Master or equivalent) in computer science or a related discipline (e.g., statistics, operations research or management science with a specialization in data and/or process science)and you are eager to become a data science researcher.
- You have proven to belong to the top of your graduating class as evidenced by your marks and supported by your references.
- 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.
- You are ambitious, but at the same time a team player.
- 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 be involved in research projects with industrial partners that provide data and give feedback on research results.
- You will supervise 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 work towards a PhD thesis in a 4 year period.
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). You will be guided towards a PhD in one of these exciting areas (depending on your background and interests).
What we offer
The position is auf 1 Jahr and is to be filled as soon as possible. An extension to 4 years in total is intended. This is a full-time position. It is also available as part-time employment per request.
The successful candidate has the opportunity to pursue a doctoral degree.
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