Research Assistant / Associate (f/m/d)



Mara Nitschke



+49 241 80 21902



Our profile

The Process and Data Science group, headed by Prof. Wil van der Aalst, is a 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 Alexander von Humboldt Professorship. 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.

Your profile

  • 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 know about process mining e.g., read the process mining book or took the Coursera MOOC "Process Mining: Data science in Action".
  • 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 language skills (English) and eager to present your ideas.

Your tasks

  • 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).

Our offer

  • The position is to be filled as soon as possible and is temporary for 4 years. The position is for 1 year with extension to further 3 years is possible.
  • This is a full-time position.
  • There is the possibility of a doctorate.
  • The position is rated EG 13 TV-L.

RWTH is certified as a family-friendly university.

The RWTH offers a variety of health, counselling and prevention services (e.g. university sports) as part of a university health management programme. There is also an extensive range of continuing education opportunities and a job ticket is offered.

The job advertisement is aimed at all genders.

At RWTH Aachen University, we particularly want to promote the careers of women and therefore welcome female applicants. Women will be given preferential consideration in cases of equal suitability, ability and professional performance, provided that they are underrepresented in the organisational unit and provided that reasons relating to the person of a competitor do not prevail.

Applications from suitable severely disabled persons are expressly welcome.

In the interest of equal treatment, please refrain from submitting an application photo.

Information on the collection of personal data in accordance with Articles 13 and 14 of the General Data Protection Regulation (DS-GVO) can be found at

Please send your application by October 31, 2023 to

RWTH Aachen University
Informatik 9 - Process and Data Science
Ahornstraße 55
52074 Aachen

You are also welcome to send your application by e-mail to . Please note that threats to confidentiality and unauthorised access by third parties cannot be ruled out when communicating by unencrypted e-mail.