Research Assistant / Associate (f/m/d)



Mara Nitschke



+49 241 80 21902



Our profile

The Process and Data Science chair, headed by Prof. Wil van der Aalst, is a research institution at RWTHTH that focuses on the interaction of processes and data. PADS represents RWTH's ambitions in the field of Data Science and is supported by the Alexander von Humboldt Professorship. PADS encompasses all topics in which discrete processes are analysed, redesigned and / or supported in a data-driven way. Process-centricity is a combination of data science techniques such as machine learning, data mining, visualisation and Big Data Infrastructures. The focus is on process mining including process discovery, conformance testing, performance analysis, predictive analytics, operations support and process improvement. This is combined with related disciplines such as operations research, algorithms, discrete event simulation, business process management and workflow automation. The chair holder is the founder of the process mining discipline and one of the world's leading computer scientists. His ambition is to realise scientific breakthroughs that help organisations derive business and societal value from event data. Investments from RWTH, the Alexander von Humboldt Foundation and the Fraunhofer Institute for Applied Information Technology make it possible to realise this and give you the unique chance to do scientific work and a PhD in the field of process mining.

Your profile

You have a university degree (Master's or comparable) in computer science or a related discipline, for example statistics, operations research or management science with a specialisation in data and/or process mininig, and are aiming to work as a research assistant in the field of data science.

You have a very good degree and can prove this with your certificates and references.

You have a quick grasp of the subject and work in a committed, autonomous and creative manner. You are familiar with process mining (e.g. have read the process mining book or successfully completed the Coursera MOOC "Process Mining: Data science in Action"). You have a genuine interest and/or experience in process mining and are willing to demonstrate this as part of the application process. You have excellent analytical skills and are willing to turn your ideas into software. You are ambitious and at the same time a team player. You have very good language skills (English) and enjoy presenting your ideas.

Your tasks

You conduct state-of-the-art research in the field of process mining in one of the top groups in data science.

You take a leading role in research projects with industry partners who provide you with data and feedback on research results. You will supervise Bachelor and Master students working in your topic area and participate in teaching at times. You present your work at national and international conferences and publish articles in the leading journals in your discipline. You produce a doctoral thesis within 4 years. Within the PADS group, four smaller subgroups work on fundamentals of process mining, dealing with large/distributed/streaming/uncertain event data, automated operational process improvement, and 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 for an employee.

The position is to be filled as soon as possible and is limited for 1 year. An extension for another 3 years is planned. This is a full-time position. Part-time employment can be arranged on request. There is the possibility of a doctorate. The position is rated TV-L EG 13.

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 May 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.