Research Assistant/Associate (f/m/d) - PhD student
Software Engineer in the area of Data and/or Process Science
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Lehrstuhl für Process and Data Science
The Process and Data Science (PADS) group, headed by Prof. Dr. Ir. 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 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. Software development plays a key role in the success of the PADS group. Therefore, we are looking for talented software engineers specializing in data science.
- 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).
- You have experience in realizing complex software, preferably related to data processing.
- You have experience in using modern database systems. Experience with Big data platforms like Apache Big Data Stack, Hadoop, Spark, Cloudera / Hortonworks is preferable.
- You have a genuine interest (or experience) in process mining, data science, process management, machine learning, etc.and are willing to demonstrate this as part of the application process.
- You are eager and able to co-supervise students working on software-intensive projects.
- You have excellent communicative skills (also in English). Experience with commercial ERP systems (SAP, etc.), process mining software (Celonis, etc.), and (robotic) process automation (UiPath, etc.) is valued.
Your Duties and Responsibilities
- You will design, develop, and maintain software for cutting-edge research in data science.
- You will contribute to open-source data-science platforms like ProM, RapidMiner, R, etc.
- You will work with industrial partners that provide data and give feedback on research results.
- You will guide PhD, Bachelor and Master students developing software and have a limited involvement in teaching.
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.
An extension to further 3 years is planned.
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.
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.
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 http://www.rwth-aachen.de/dsgvo-information-bewerbung.
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Lehrstuhl für Process and Data Science
Applicants are invited to submit their applications via email. For data protection reasons, however, we recommend sending applications via mail.