Postdoctoral Position in Counterfactual Explanations for Multivariate Time Series ENSEA in France

PhD Candidate in Machine Learning for Temporal and Spatiotemporal Data The Department of Computer Science at the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway, invites applications for a four-year PhD position in machine learning. The project is part of STRIDE, an interdisciplinary initiative studying the resilience of transport systems under disruptions. The research will develop deep-learning methods for temporal and spatiotemporal data, including multivariate time...

This PhD project at the Department of Computer Science, Norwegian University of Science and Technology (NTNU) focuses on machine learning for temporal and spatiotemporal data , including time series and multivariate time series observed on graph nodes and edges. The research is centered on forecasting and on detecting disruptions in data drawn from complex networked systems. The position is embedded in STRIDE , an interdisciplinary NTNU project on the resilience of transport systems. Transport n...

Postdoctoral Researcher in Data Science & Machine Learning for Financial Fraud Detection at Université d'Orléans (France). This postdoctoral position is hosted by the Laboratoire d'Économie d'Orléans (LEO) and focuses on developing interpretable and operational machine learning and deep learning methods for fraud detection across insurance, social contributions, and banking. The project addresses major practical challenges in detecting anomalous behaviour, suspicious networks, and emerging fraud...

This postdoctoral position at Université Côte d'Azur focuses on robust decision-making under distribution shift and statistical uncertainty. The successful candidate will develop new theoretical and methodological approaches aimed at improving robustness in uncertain and changing environments. The project combines theory, statistics, and algorithmic development. The postdoctoral researcher will study the mathematical and statistical properties of the proposed methods, with attention to convergen...

This six-month Master’s/Engineering internship at the I3S Laboratory of Université Côte d’Azur in Sophia Antipolis, France, focuses on developing world-model approaches for tabular data and radiomics. The project will investigate self-supervised learning architectures, particularly the Joint Embedding Predictive Architecture (JEPA) , for structured data organized in rows and columns. The work will examine how JEPA can be adapted to tabular datasets and will study recent approaches such as T-JEPA...