Research Assistant/Associate - Doctoral Candidate (f/m/d)



Mara Nitschke


+49 241 80 21902



Lehrstuhl für Process and Data Science (Informatik 9)

Our Profile

The Process and Data Science Group, headed by Prof. Wil van der Aalst, is one of the research units in the Department of Computer Science. The scope of PADS includes all activities 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. The group’s research and teaching activities can be characterized by the keywords: Data Science, Process Science, Process Mining, Business Process Management, Data Mining, Process Discovery, Conformance Checking, and Simulation.

The group has been established in the context of the Alexander von Humboldt Professorship awarded to Prof. Wil van der Aalst in 2017. The award is Germany’s most prestigious and valuable prize for international researchers. The PADS group supports RWTH’s strategy to further strengthen its Data Science capabilities. The group also closely collaborates with the Fraunhofer Institute for Applied Information Technology (FIT).

Currently, the main research 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.

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 (f/m/d).
  • 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 Duties and Responsibilities

  • 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, conï¬dentiality, 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 successful candidate will be employed under a regular employment contract.
The position is to be filled at the earliest possible date and offered for a fixed term of 1 year..
The option to extend the contract to four years is planned and desirable.
The fixed-term employment is possible as it constitutes one of the fixed-term options of the Wissenschaftszeitvertragsgesetz (German Act on Fixed-term Scientific Contracts).
This is a full-time position with the possibility of a part-time contract upon request.
It is possible to adjust the number of hours per week.
The successful candidate has the opportunity to pursue a doctoral degree in this position.
The salary is based on the German public service salary scale (TV-L).
The position corresponds to a pay grade of EG 13 TV-L.

About us

RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. Employees who are covered by collective bargaining agreements and civil servants have access to an extensive range of further training courses and the opportunity to purchase a job ticket.
RWTH is an equal opportunities employer. We therefore welcome and encourage applications from all suitably qualified candidates, particularly from groups that are underrepresented at the University. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is strongly committed to encouraging women in their careers. Female applicants are given preference if they are equally suitable, competent, and professionally qualified, unless a fellow candidate is favored for a specific reason.
As RWTH is committed to equality of opportunity, we ask you not to include a photo in your application.
You can find information on the personal data we collect from applicants in accordance with Articles 13 and 14 of the European Union's General Data Protection Regulation (GDPR) at

Application deadline:31/03/2024
Mailing Address:RWTH Aachen University
Lehrstuhl für Informatik 9 (Process and Data Science)
Mara Nitschke
Ahornstraße 55
52074 Aachen
Applicants are invited to submit their applications via email. For data protection reasons, however, we recommend sending applications via mail.