Researcher in Explainable AI and Human-Machine Interaction

2 weeks ago

Dublin, Dublin City, Ireland beBeeExplainableAI Full time €48,996
Job Opportunity

We are seeking a highly skilled Post-Doctoral Researcher to join our interdisciplinary team working on innovative projects that integrate human factors and explainable AI. Your primary responsibility will be to conduct research in human-machine interaction, safety-critical systems, and alarm management.

The ideal candidate will have a PhD in a relevant field, such as Human Factors, Control Engineering, Computer Science, or Artificial Intelligence. They should demonstrate expertise in empirical human performance data collection, knowledge of Bayesian networks, and strong programming, data analysis, and modelling skills.

You will work closely with academic, industrial, and international partners, contributing to high-quality publications and presentations. The role also involves public outreach and engagement with centre activities.

We value diversity and encourage applications from everyone, regardless of background. Our goal is to create an inclusive and supportive environment for all staff members.

Key Responsibilities
  • Conduct research in human-machine interaction, safety-critical systems, and alarm management.
  • Develop and implement novel methods for explainable AI decision support.
  • Collaborate with partners across academia, industry, and internationally.
  • Publish high-quality research papers and present at conferences.
  • Engage in public outreach and contribute to centre activities.
Requirements
  • PhD in Human Factors, Control Engineering, Computer Science, Artificial Intelligence, or a related discipline.
  • Demonstrated research expertise in human-machine interaction, explainable AI, or safety-critical systems.
  • Experience with empirical human performance data collection (e.g., eye tracking, physiological monitoring, workload assessments).
  • Knowledge of Bayesian networks.
  • Strong programming, data analysis, and modelling skills.
  • Evidence of high-quality peer-reviewed publications and conference presentations.
  • Ability to work independently and collaboratively in an interdisciplinary team.

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