We are seeking a Postdoctoral Researcher to lead innovative research investigating human interactions with advanced Decision Support Systems (DSS) integrated with Artificial Intelligence and Machine Learning (AI/ML). Rooted in a human-centered design (HCD) philosophy, this project explores the critical intersection of user interface design, varying levels of machine autonomy, and human cognitive performance. The successful candidate will design and conduct empirical studies to understand how different interface modalities and automation levels—including operator-controlled autonomy—impact decision-making, risk management, and overall human-machine team performance, ensuring that the technology is designed around human needs, capabilities, and operational contexts.

 Areas of Interest:

• Human-Centered Design Integration: Applying iterative HCD methodologies (e.g., user research, task analysis, and rapid prototyping) to ensure that the AI-enabled DSS enhances, rather than hinders, human performance.
• Interface Modalities: Investigating the impact of alternatives to traditional text-based UIs (e.g., visual, spatial, auditory, or multimodal interfaces) on the speed, accuracy, and quality of human decision-making.
• Cognitive Assessment: Evaluating the effects of these novel interfaces on human metacognition (such as the calibration of trust and situational awareness), mental workload, and overall cognitive load.
• Levels of Autonomy: Analyzing how varying the level of automation or autonomy granted to the AI/ML agents within the DSS alters the operator's cognitive state, workload, and metacognitive processes over time.
• Operator-Controlled Autonomy & Risk: Investigating the impact of providing users with direct control over the level of automation. This includes assessing how adjustable autonomy influences overall human-machine performance, operator risk tolerance, dynamic risk management strategies, and subjective user preference.

To conduct the research a suite of behavioral and physiological tools is available (eye tracking, EEG, biometric sensors). The team is interdisciplinary with psychologists, computer scientists and developers.

Reference Literature:
Li, H., Wang, Y., Lia, Q.V., & Qu, H. (2025). Why is AI not a panacea for data workers? An interview study on human-AI collaboration in data storytelling. IEEE Transactions on Visualization and Computer Graphics, 31(10). 

Berretta, S., et al. (2023). Defining human-ai teaming the human-centered way: A scoping review and network analysis. Frontiers in Artificial Inteliigence, 6:1250725. doi: 10.3389/frai.2023.1250725

cognitive psychology, decision making, metacognition, human-centered design, cognitive science, human-machine teams

citizenship

Open to U.S. citizens and permanent residents

level

Open to Postdoctoral applicants

Additional Benefits

relocation

Awardees who reside more than 50 miles from their host laboratory and remain on tenure for at least six months are eligible for paid relocation to within the vicinity of their host laboratory.

health insurance

A group health insurance program is available to awardees and their qualifying dependents in the United States.