You will take on one of the most ambitious topics in the field of industrialization: digitalization and artificial intelligence (AI) with autonomous machines, sensor data, and decision support systems. The challenge remains that despite technological advances, the use of AI technologies remains below expectations in industry practice. Effective use of these novel technologies would enable precision farming and manufacturing as well as sustainable intensification, which can have profound impacts on climate change and economic performance. In this PhD project, you will explore a rich contextual understanding of human-AI interactions. Shining light into the interactions of manual laborers and AI will contribute novel understanding of how human-AI configurations at work emerge.
The research carried out during this PhD assignment is expected to contribute to theoretical advancements and practical applications. Tasks the candidate is expected to execute include:
- Identify problems and set an agenda for future research on AI in manufacturing and agriculture;
- Deepen the understanding of human-AI work through fieldwork, including qualitative (interviews), quantitative (experiments, surveys), and/or computational (digital traces) approaches;
- Advance theory on digital transformation of work from manual labour to knowledge worker;
- Develop and validate technical and organizational interventions that help industrial SMEs adopt novel AI-based technologies successfully;
- Equip SMEs with the necessary knowledge and skills to effectively use AI and succeed in times of machine learning and AI.
As a doctoral student, your key responsibilities will be to manage and carry out research projects within 48 months and write a PhD thesis. You will participate in research and training activities and disseminate research in the scientific community (international journals and conferences) and non-scientific community by outreach and public engagement.
You will also be responsible for taking courses per the research education and liaising with the other research staff, students, and partner institutions working in broad areas relevant to the research project.
Participation in other department duties, such as meetings, or teaching, is expected to cover a maximum scope of 20%.