Job offer

As AI systems evolve from individual assistants into teams of interacting agents, a central challenge is understanding how humans can work effectively with these systems, maintain appropriate levels of trust and control, and make informed decisions without becoming overwhelmed by information and interaction demands.

The successful candidate will contribute to research on human-centered methods for adaptive collaboration between humans and AI agents. A central component of the position will be the empirical investigation and evaluation of human-AI collaboration through controlled experiments and, where appropriate, longitudinal studies involving human participants. The research will examine how individual differences, team composition, agent capabilities, and interaction patterns influence collaboration, decision quality, and human experience. The research agenda will also consider how principles of trustworthy and socially aware AI, including fairness, transparency, and norm-sensitive behavior, can support effective human-AI collaboration.

The position will be supported primarily by a Horizon Europe research project, alongside other research funding.

This position offers the opportunity to contribute to an emerging research area at the intersection of agentic AI, human-AI interaction, and empirical evaluation; develop original research ideas; publish at leading international venues; and collaborate with researchers across ELLIS and the wider international research community.

PhD or equivalent, * PhD in Computer Science, Artificial Intelligence, Human-Computer Interaction, Cognitive Science, or a closely related field. Candidates who have completed their PhD or expect to complete it before the start date are welcome to apply.

• Strong research expertise in one or more relevant areas, such as human-AI interaction, human-AI collaboration, agentic AI, multi-agent systems, machine learning, or the empirical evaluation of AI systems.
• Strong programming skills and practical experience with modern machine learning frameworks, AI systems, or computational methods relevant to the research agenda.
• Experience in empirical research, including the design, execution, or analysis of experiments or user studies.
• A strong research track record, demonstrated through publications and other relevant research contributions appropriate to career stage.

Specific Requirements

The following will be considered advantages:

• Experience developing, evaluating, or deploying LLM-based agents and multi-agent AI systems.
• Knowledge of experimental design, cognitive load measurement, behavioral analysis, or human decision-making.
• Experience with adaptive interfaces, mixed-initiative interaction, human-AI teaming, or research on trust and reliance in AI systems.
• Familiarity with trustworthy AI, fairness, responsible AI, or norm-aware agent behavior.
• Experience conducting longitudinal studies or analyzing complex human-subject data.
• Experience with project coordination, scientific dissemination, mentoring, or organizing academic events.

Candidates with publications at leading venues in relevant fields, such as NeurIPS, ICML, ICLR, ACL, AAAI, IJCAI, AAMAS, CHI, CSCW, IUI, ACM CHI, ACM CSCW, ACM/AAAI AIES and ACM FAccT, are particularly encouraged to apply., * Strong analytical, critical-thinking, and creative problem-solving skills.

• Ability to formulate research questions, develop original ideas, and pursue them independently.
• Excellent written and spoken English, including the ability to communicate complex research findings clearly.
• Strong interpersonal and collaboration skills, with the ability to work effectively in an interdisciplinary and international environment.
• Initiative, intellectual curiosity, sound research judgment, and a commitment to scientific integrity and responsible research.
• Motivation to contribute to a collaborative research culture and to the broader scientific community.

Languages ENGLISH

Level Excellent

Research Field Computer science » Other

Years of Research Experience 4 - 10