PhD Fellow in Human-Computer Interaction with Explainable AI

This PhD Fellow position in Human-Computer Interaction (HCI) with a focus on Explainable Artificial Intelligence (AI) requires advanced research capabilities in both HCI principles and AI technologies. Candidates should have a strong foundation in human-centered design, user experience evaluation, and interaction techniques to effectively study and improve how users engage with AI systems. Expertise in Explainable AI is essential, including knowledge of interpretable machine learning models, methods for generating transparent AI explanations, and the ability to critically assess the impact of explainability on user trust and decision-making. The role demands proficiency in programming languages commonly used in AI research such as Python, and familiarity with AI frameworks and libraries for developing and testing explainability approaches. Analytical skills for conducting empirical user studies, data analysis, and usability testing are important. Given the academic nature of the position, candidates should demonstrate experience or strong interest in publishing research findings, collaborating in interdisciplinary teams, and contributing to scientific advancements at the intersection of AI and HCI. A doctoral-level education or equivalent research experience in computer science, cognitive science, or a related field is implied. Overall, the role combines technical expertise in AI and software development with a deep understanding of human factors and interaction design, aiming to create AI systems that are not only powerful but also transparent and user-friendly.