Research Associate (f/m/d)
in Natural Language Understanding, Knowledge Graphs, or Machine Learning
Institute of Applied Informatics and Formal Description Methods (AIFB)
KIT is one of the world’s leading research institutions in the field of technology. The Web Science research group at the KIT Institute AIFB is known worldwide for its research in the field of knowledge representation and, under the direction of Dr. Färber, deals with data science topics. The research group’s focus is on the development and application of artificial intelligence (AI) methods. The core topics include natural language processing (e.g., information extraction), the semantic representation of knowledge through knowledge graphs, machine learning (e.g. for search and recommender systems), and the combination of these topics.
The research group works closely with the Information Process Engineering (IPE) research division of the FZI Research Center for Computer Science (FZI). There are also numerous connections to national and international research institutions and companies. An excellent infrastructure with servers and high-performance computers (e.g. HoreKa, one of the 15 fastest computers in Europe) is available for research.
- Performing research in at least one of the following areas: natural language understanding/natural language processing, knowledge graphs, machine learning.
- Contributing to national and international research projects, often with industry partners.
- Participation in teaching (e.g., organizing seminars and exercises for lectures in English, as well as for German if applicable).
- Presentation of research results and prototypes in the context of publications and talks at national and international level.
The opportunity for a doctorate is given.
zum nächstmöglichen Zeitpunkt / as soon as possible
- A very good completed or almost completed master’s degree in computer science, business informatics, industrial engineering, computational linguistics, mathematics, or a related subject.
- Expertise in natural language understanding/natural language processing, knowledge graphs, or machine learning.
- A high degree of personal responsibility, motivation, commitment, and excellent teamwork skills.
- Good knowledge of English and presentation skills.
The remuneration occurs on the basis of the wage agreement of the civil service in TV-L E13, depending on the fulfillment of professional and personal requirements.
limited to one year with an option to extend for a further three years
Application up to
December 31, 2021
Contact person in line-management
For further information, please contact Dr.-Ing. Michael Färber, email: firstname.lastname@example.org.
Please send your detailed application with cover letter, CV, copies of degrees and certificates in one PDF file in electronic form to:
Dr. Michael Färber, email@example.com and
Beate Kühner, firstname.lastname@example.org
vacancy number: 2181/2021
We prefer to balance the number of employees (f/m/d). Therefore, we kindly ask female applicants to apply for this job.
Recognized severely disabled persons will be preferred if they are equally qualified.