Postdoc researcher in explainable artificial intelligence and machine learning at ITEC, an imec research group at KU Leuven

Postdoc researcher in explainable artificial intelligence and machine learning at ITEC, an imec research group at KU Leuven

The research group ITEC, is looking for a postdoc researcher in explainable artificial intelligence and machine learning to carry out strategic basic research in artificial intelligence and machine learning with potential applications and impact in the field of education and training (technology-enhanced personalized learning) and in the field of health (personalized medicine).

In interaction with the principal investigators (professors) and research management team at ITEC, the candidate co-supervises and further develops the AI and machine learning research line within the different application domains, and carries out pioneering research him/herself. This will involve collaboration across the disciplines within ITEC, and may also involve collaboration with companies (hospitals, training organizations, as well as technology companies). In this context, the candidate will co-supervise ITEC’s PhD candidates in AI and machine learning, and will interact with post-docs in the other disciplines at ITEC (in particular in statistics). The candidate is expected to actively participate in the recruitment of projects, and to publish the results of the research in scientific journals and present them at international and local conferences.

The candidate will interact with researchers active in health and education. In the health domain, we are primarily focusing on clinical decision support systems. These tools often involve risk prediction models for medical conditions, where both accuracy and interpretability are of high importance. In the domain of education and training, we focus on decision support for learners and teachers/experts, and develop novel techniques for recommending learning tasks matched to the skills and interests of learners, for automated assessment of learning tasks that involve multiple skills (e.g. essays), and for predicting dropout in learning environments that require high self-regulation (e.g. MOOCs). In this domain, the candidate interacts with researchers in imec’s Smart Education research programme, both within ITEC and with research groups of at the universities of Ghent (UGent) and Brussels (VUB), as well as with imec. One research direction that is important in both application domains is time-to-event prediction (survival analysis), which is on the border between statistics and machine learning, and will be of great importance for this function.

ITEC is a research group at KU Leuven and imec, Flanders’ high-tech research and innovation hub for nanoelectronics and digital technologies. On the campus Kortrijk of the KU Leuven, ITEC unites researchers from three different faculties (Psychology & Educational Sciences, Arts and Medicine) and four disciplines (educational psychology, statistics, applied linguistics, computer science). Researchers at ITEC conduct both fundamental and applied research on the design, development, and evaluation of personalized and adaptive digital solutions, aimed at helping experts and end users to make effective decisions informed by data analysis and visualizations. Primary application domains include education and training, media, and health. The main focus of the AI and machine learning subgroup of ITEC is to apply existing and develop new machine learning algorithms to advance the application domains. In particular, we focus on supervised, unsupervised and semi-supervised learning. Key activities in the group relate to multi-label/target prediction, recommender systems, active learning, survival analysis and longitudinal data analysis; always with a specific attention to interpretability to increase trust in the AI models.

ITEC is a research group at KU Leuven and imec, Flanders’ high-tech research and innovation hub for nanoelectronics and digital technologies. On the campus Kortrijk of the KU Leuven, ITEC unites researchers from three different faculties (Psychology & Educational Sciences, Arts and Medicine) and four disciplines (educational psychology, statistics, applied linguistics, computer science). Researchers at ITEC conduct both fundamental and applied research on the design, development, and evaluation of personalized and adaptive digital solutions, aimed at helping experts and end users to make effective decisions informed by data analysis and visualizations. Primary application domains include education and training, media, and health. The main focus of the AI and machine learning subgroup of ITEC is to apply existing and develop new machine learning algorithms to advance the application domains. In particular, we focus on supervised, unsupervised and semi-supervised learning. Key activities in the group relate to multi-label/target prediction, recommender systems, active learning, survival analysis and longitudinal data analysis; always with a specific attention to interpretability to increase trust in the AI models.

• The applicant must have obtained a PhD in machine learning, artificial intelligence, computer science, statistics or related fields.
• Excellent command of English is necessary (both written and orally). Knowledge of Dutch is considered a strong asset.
• Research experience in machine learning for education and training, or in another application domain within ITEC’s focus, is considered an asset.
• Research experience in time-to-event analysis or another key activity investigated in ITEC’s AI and machine learning subgroup is considered a strong asset.
• Strong publication record.
• Experience with grant writing is considered an asset.
• Strong communication skills, leadership skills, high flexibility and a real team player.

KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR [at] kuleuven[.]be.