Research Associate (f/m/d) Neurosymbolic AI
The research group Web Science/en deals with the development and application of artificial intelligence (AI) methods. This includes the semantic representation of knowledge through knowledge graphs, machine learning, and the processing of natural language.
Your activities include research in the field of symbolic methods for neurosymbolic AI for robotics in a soon-to-be-confirmed research project together with a renowned German AI startup in the field of Large Language Models (LLMs). In addition to research work, you will also be active in teaching and you participate in science administration.
There is the possibility of pursuing a doctorate.
You have a degree (Master's/Diploma (University)) in Industrial Engineering and Management, Informatics/Computer Science, Business Informatics, or in related fields. Ideally, you have experience in:
- Semantic Technologies
- AI planning
and you are interested in:
- Large Language Models
Programming experience is highly advantageous. On top, you can excel using a high level of self-motivation and the ability to work in a team. A very good command of the English language in speech and writing completes your profile. Proficiency in German is very welcome.
The remuneration occurs on the basis of the wage agreement of the civil service in EG-13, depending on the fulfillment of professional and personal requirements.
as soon as possible
For further information, please contact Dr. Tobias Käfer/en.
Please apply with your relevant documents (letter of motivation, curriculum vitae, certificates, if possible with master’s thesis or its draft and GitHub profile). You can hand in your application using KIT's application system. See also the official version of this job ad. The positions are open until filled.
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.
PhD-Students / Research Associates
No information available