Research Assistant/Associate (w/m/d)

Postdoc

Contact

Name

Natasa Marcanova

Telephone

workPhone
+49 241 80 21902

E-Mail

Institution

Computer Science 9 - chair in Process and Data Science

Our Profile

The Process and Data Science (PADS) group, headed by Prof. Dr. Ir. 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
a recently awarded Alexander von Humboldt Professorship (Germany’s most valuable international research award with value of 5
million euros). 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 ambitious Postdocs.

Your Profile

You have a PhD 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 proven to be an independent and strong researcher (supported by a good publication track record).
You are a fast learner, dedicated, autonomous and creative.
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 together with PhDs and Master students.
You are ambitious, but at the same time a team player.
You are eager and able to (co-)supervise PhD students and take a very important role in research projects.
You have excellent communicative skills (also in English).

Your Duties and Responsibilities

You will do cutting-edge process mining research in one of the top groups in data science.
You will take a important role in research projects with industrial partners that provide data and give feedback on research results.
You will supervise PhD, 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 publish in the leading journals in your discipline.
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). The postdocs are expected to take a powerful role in these subgroups and co-supervise PhDs working in these group.

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 for 1 year. The goal is further qualification, especially in the scientific field of process mining. An extension to another 3 years is possible. The habilitation is not excluded.
This is a full-time position with the possibility of a part-time contract upon request.
Applicants must have a doctorate/Ph.D. or equivalent.
The salary corresponds to pay grade EG 13 TV-L of the German public service salary scale (TV-L).
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. We also offer a comprehensive continuing education scheme and a public transportation ticket available at a significantly reduced price.
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

Application
Number:32333
Application deadline:30.11.2020
Mailing Address:RWTH Aachen
Informatik 9 - PADS
Prof. Dr. Wil van der Aalst
D-52056 Aachen
Email:
Applicants are invited to submit their applications via email. For data protection reasons, however, we recommend sending applications via mail.