Are you looking for an exciting PhD position at the interface of Digital Work, Digital Learning and Artificial Intelligence? In our research project "Hybridization of Human and Artificial Intelligence in Knowledge Work ( HyMeKI )" we are working on the development and testing of digital assistance systems and innovative digital collaboration forms that promote human and machine learning. 

Two PhD positions are available in the HyMeKI research project:

• Jobprofile "Digital assistance systems for AI-based teaching-learning formats" focuses, among other things, on the personalization of human learning processes based on learning paths, learning types and prior knowledge of the learner.

• Job profile "Learning digital assistance systems" focuses among other things on process-integrated learning-by-feedback approaches with which both the knowledge base of the system and the end user can be expanded.

Framework data

• Start of employment: 01.01.2022 or by agreement
• Pay grade: EG 13 TV-H
• Scope of employment: full-time (currently 40 hours per week)
• Time limit: the positions are initially limited until 30.09.2024.

What awaits you...

• A wide range of personal development and training opportunities
• Research and work in an interdisciplinary, dynamic team with a pleasant working atmosphere
• Integration into a research group with intensive doctoral supervision
• Independent project work in a research area of high theoretical and practical relevance
• and much more...

For further inquiries please contact Dr. Sarah Oeste-Reiß(oeste-reiss[at]uni-kassel[dot]de) and Prof. Dr. Jan Marco Leimeister(leimeister[at]uni-kassel[dot]de).

Here you can download the job advertisement "Learning digital assistance systems", focus among other things on process-integrated learning-by-feedback approaches with which both the knowledge base of the system and the end user can be expanded (reference number  34519 ).

Here you can download the job advertisement "Digital assistance systems for AI-based teaching-learning formats", focus among other things on the personalization of human learning processes based on learning paths, learning types and prior knowledge of the learner (Reader Service Code  34520).