Olivier Caelen

PhD opportunity in Machine Learning, Statistics, and Trustworthy AI at UCLouvain (LIDAM / ISBA), Belgium, under Prof. Olivier Caelen . The project focuses on developing differentiable calibration losses for multi-class models to improve the reliability of neural network probabilities, going beyond standard post-hoc calibration approaches. This is a strong fit for candidates interested in deep learning , statistics , trustworthy AI , and probabilistic model calibration. Eligibility highlights include a Master’s degree in Computer Science, Mathematics, Statistics, or Data Science, along with solid machine learning knowledge, Python programming skills, and English proficiency. The post indicates a start date of October 2026 . No funding details or application deadline are provided in the post excerpt. Interested applicants should consult the UCLouvain ISBA information page and follow the linked announcement for further application instructions.

PhD Position on Causal AI for Smart Buildings at UCLouvain (LIDAM). This opening is for an applied PhD project at the intersection of temporal causal inference , machine learning , and building energy systems . The research is described as a collaboration with an industrial partner, with time split equally between the university and the industrial environment, which suggests a strongly applied and translational research setting. Research themes: causal AI, smart buildings, energy systems, temporal modeling, applied machine learning. Supervisor/announcer: Olivier Caelen, Associate Professor at UCLouvain. Eligibility/requirements: The post does not list formal entry requirements, but it is aimed at students interested in PhD-level research in AI and energy-related systems. Funding: No stipend, tuition, or scholarship details are provided in the post. Deadline: Thursday, 10 September 2026. If you are interested, monitor the original LinkedIn post or related UCLouvain/LIDAM channels for the full application instructions.