Are you interested in investigating how teams collaborate with AI-systems at work, to understand when and why users are (un)willing to adopt these systems in their work routines, and what happens when things don't go as planned?

Come join our international and interdisciplinary team to research the future of teamwork.

The project
In many organizations and across industries, artificial intelligence (AI) is transforming the way we work. AI-systems are implemented to assist employees with decision making, to decrease workload, or to increase efficiency. As their level of intelligence increases, collaboration between humans and AI systems becomes more common and interdependent. Consequently, the role of the AI changes, transforming from a technology used as a tool to full team members.

Especially in non-routine or disrupted conditions, team collaboration in human-AI teams may unfold differently compared to all-human teams. On the one hand, AI may allow for better adaptive responses, but there may also be negative consequences, for example when the AI's input is ignored or circumvented. But what happens when we get more used to these new types of teams? Will human and AI teammates be able to develop mutual understanding and trust?

To successfully implement human-AI teams in organizational settings, it is critical to understand how users adapt to these new collaborative settings. The goal of this PhD-project is to address these issues by answering the following questions:
(1) How does shared cognition and trust in human-AI teams develop?
(2) How do human-AI teams adapt to change?

Your role in this project

Within this project, you will:

• further develop the project proposal based on academic literature, and in collaboration with industry partners
• design and execute empirical (field) studies
• design and execute lab/online experiments
• statistically analyze data obtained from field studies and experiments and report on results
• communicate practical implications of your research to specific stakeholders/the general public
• present the findings of your research at (inter)national scientific conferences
• conduct research at one of our collaborators' universities abroad
• publish papers in internationally renowned academic journals

The Human Performance Management (HPM) Group of the School of Industrial Engineering, in collaboration with the Eindhoven Artificial Intelligence Systems Institute (EAISI), is looking for a PhD-student on human-AI collaboration at work (4-years; 1.0 FTE).

The School of Industrial Engineering is one of the longest-established IE Schools in Europe, with a strong presence in the international research- and education community, and an extensive network of industrial partners. Operations Management and Operations Research are at the core of the undergraduate IE program. The graduate programs (MSc and PhD) in Operations Management & Logistics and in Innovation Management attract top-level students from all over the world. Researchers participate in industrial activities with members of, amongst others, the European Supply Chain Forum.

Human Performance Management (HPM) at TU/e develops scientific knowledge and tests theories that uncover and explain (psychological) processes contributing to performance at the organizational, team, and individual level. By examining the 'people factor' in operational and innovation processes, HPM aims to ensure that employees can help in bringing organizational strategies to fruition in the most rewarding and efficient way possible.

The Eindhoven AI Systems Institute (EAISI) combines all TU/e Artificial Intelligence activities. Top researchers from various research groups work together to create new and exciting AI methodologies and applications with a direct impact on the real world. TU/e has been active in the field of AI for many years, which gives the new institute an excellent starting position to build upon.

• Recently completed (or be close to completion of) a Master's degree in Work & Organizational Psychology, Management Science, Cognitive Science, Industrial Engineering, or related fields.
• Demonstrable experience in conducting empirical and/or experimental research, including knowledge of and demonstrable experience with applying (state of the art) statistical techniques.
• Demonstrable affinity with relevant topics, such as AI, teams, trust, and/or adaptation is appreciated.
• Good organizational skills and a proactive work orientation.
• Excellent mastering of the English language and good communication and writing skills. Note that there is no Dutch language requirement.

• A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
• A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
• To develop your teaching skills, you will spend 10% of your employment on teaching tasks.
• To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program).
• A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
• Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
• Should you come from abroad and comply with certain conditions, you can make use of the so-called '30% facility', which permits you not to pay tax on 30% of your salary.
• A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
• Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.