Research Assistant / Associate

for the Projects «BridgingAI» or «AIStudyBuddy»

Contact

Name

Natasa Marcanova

Telephone

workPhone
+49 4218021902

E-Mail

Institution

Informatik 9 - Process and Data Science

Our Profile

The Process and Data Science group, headed by Prof. 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 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 and to provide unique opportunities for a talented student do PhD research in process mining.

Your Profile

oYou 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.
oYou have proven to belong to the top of your graduating class as evidenced by your marks and supported by your references.
oYou are a fast learner, dedicated, autonomous and creative.
oYou know about process mining (e.g., read the process mining book https://www.springer.com/de/book/9783662498507 or took the Coursera MOOC "Process Mining: Data science in Action" https://www.coursera.org/learn/process-mining).
oYou have a genuine interest (or experience) in process mining and are willing to demonstrate this as part of the application process.
oYou have excellent analytical skills and you are willing to implement your ideas in software.
oYou are ambitious, but at the same time a team player.
oYou have excellent German and good Englisch language skills.

Your Duties and Responsibilities

The PADS group was successful with both an individual and a collaborative application in the federal-state initiative to promote artificial intelligence in higher education (total 5.8 million euro). The projects combine Process Mining, AI, and Learning Analytics. The two projects are «BridgingAI» and «AIStudyBuddy». Both are coordinated by the RWTH Center for Artificial Intelligence (AI Center).

The AIStudyBuddy project (3.9 million euros) combines Learning Analytics and Process Mining. Besides RWTH, the Ruhr-Universität Bochum (RUB) and Bergische Universität Wuppertal (BUW) are working together toward using modern AI technologies to support the planning and reflection of individual courses of study.
The focus is on two target groups:
For students, the "StudyBuddy» provides informed and evidence-based planning of their studies over several semesters into the future. StudyBuddy enables advanced visualizations of study progress and provides action-oriented feedback. AI technologies are, for example, used to determine courses of studies that have led to successful completion of a degree in the past.
The second target group is the group of curriculum designers. With "BuddyAnalytics», they receive a tool that provides interactive visualizations and information for decision making. The goal is to help them improve competence-oriented curriculum development as well as advising students using data driven analytics. The project combines the AI paradigms of data-based (Process Mining) and rule-based AI (Answer Set Programming). Process mining discovers and analyzes actual study behavior using data from the Campus system, study management, and examination systems. It compares real courses of study with the intended ones.
https://www.pads.rwth-aachen.de/global/show_picture.asp?id=aaaaaaaabctuexu

The BridgingAI project (1.9 million euros) aims to make AI-related courses available to a larger audience. Educational offers related to AI are in high demand, while at the same time the numbers of students attending lectures are limited due to capacity problems. Hence, scalable solutions are required. This is where BridgingAI comes into place: Building on the existing AI expertise at RWTH University, a micro-bachelor will be developed that is conceived for students from various disciplines. This micro-bachelor aims to build a bridge curriculum at the transition from bachelor to master. The PADS group will develop two new Massive Open Online Courses (MOOCs): one MOOC on process mining and one MOOC on data science.
https://www.pads.rwth-aachen.de/global/show_picture.asp?id=aaaaaaaabctuges

See also https://www.ai.rwth-aachen.de/go/id/pmgjb?lidx=1#aaaaaaaaaapmgjd for more details.
Candidates interested in the process-mining-related positions are invited to apply via applications@pads.rwth-aachen.de using the keyword «BridgingAI» or «AIStudyBuddy». When you apply, please include relevant information and motivate why you can contribute to our research and the project. Generic applications will be discarded.

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 . An extension for further 3 years is planned.
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 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:34633
Application deadline:30.09.2021
Mailing Address:RWTH Aachen University
Informatik 9 - Process and Data Science
Ahornstraße 55
52074 Achen
Email:
Applicants are invited to submit their applications via email. For data protection reasons, however, we recommend sending applications via mail.