Research Assistant (f/m/d) - Part-time
The Process and Data Science (PADS) group, led by Prof. Dr. Ir. Wil van der Aalst, is a research group 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 Alexander von Humboldt Professorship (Germany's most valuable international research award).
PADS encompasses all topics in which discrete processes are analysed, redesigned and / or supported in a data-driven manner. 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 leader of the group 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 provide talented graduates with a unique opportunity for scientific work and doctoral studies in the field of process mining.
You aspire to work as a research assistant in the field of Data Science and have a university degree (Master or comparable) in Computer Science or a related discipline (e.g. Statistics, Operations Research or Management Science with a specialisation in Data and/or Process Mining).
You have a very good degree and can prove this with your certificates and references.
You have a quick grasp and work in a committed, autonomous and creative manner.
You have a genuine interest (and/or experience) in process mining and are willing to demonstrate this during 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 excellent communication skills (also in English).
Within the PADS group, four smaller subgroups work on process mining fundamentals, handling large/distributed/streaming/uncertain event data, automated operational process improvement and responsible process mining (focus 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).
The position is on an employment contract basis.
The position is to be filled as soon as possible and is limited for 12 months. An extension of at least 2 years is planned, for a total of 3 years is possible.
The position is part-time with half of the regular weekly working hours.
There is the possibility of a doctorate.
The position is rated TV-L 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 a comprehensive 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 http://www.rwth-aachen.de/dsgvo-information-bewerbung.
Please send your application by March 31, 2024 to
RWTH Aachen University
Informatik 9 - Process and Data Science
You are also welcome to send your application by e-mail to email@example.com. Please note that threats to confidentiality and unauthorised access by third parties cannot be ruled out when communicating by unencrypted e-mail.