We are seeking an
Assistant Professor to join our research team with expertise on the intersection of learning, artificial intelligence, and human factors in simulated environments.
The proposed position addresses a growing, interdisciplinary research area at the intersection of psychology, simulation, and artificial intelligence. The position should research and/or support the following themes:
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Human-AI interaction: Integrating psychological research methods with data science techniques, enriching our understanding how humans and AI can communicate and cooperate safely in critical domains e.g., safety in driving and transport, and safety in health.
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Exploring human cognition and behavior through simulation: Using simulated environments and settings to gain insights into human enhanced decision-making and performance in controlled, yet realistic, settings.
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Supporting Human-Centred AI development: Contributing to the design of AI systems that prioritize human needs, trust, and safety.
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Developing simulation-based training programmes: Promoting the use of simulation technologies to create adaptive, data-driven training systems for education, healthcare, and professional development.
This position is part of the SSH Sector Plan, within the theme of Human factor In New Technologies (HINT), and directly supports the University of Twente’s mission to contribute to impactful, interdisciplinary research that addresses societal challenges. It addresses the core aspects of the UT Impact Area of
Safety and Security and is linked to the
Impact Area of Health.
It also aligns with the HINT sub-groups "Make It Work," which focuses on the integration of AI systems into human daily life, and with the theme "Becoming Real," which focuses on virtual reality, simulation, and data. It is well-embedded in the CODE section focusing on data science and human factors research, and within the broader context of LDT with its focus on learning.
Research and teaching The successful candidate will pursue research that, for instance, integrates data science methods into simulation-based studies and its applications in safety-critical domains, and/or contributing to both fundamental understanding and practical applications of human-AI interaction.
The candidate should be able to teach courses in cognition and interaction with systems, human factors and basic data science methods.