Laboratoire d'informatique de l'École polytechnique

Post doc at LIX

The Big Data Analytics Team at Ecole Polytechnique is seeking a postdoc to work on the topic of “Explainable Anomaly Detection on Data Streams”. The appointment is for one year, with possible renewal for additional months.

I. Overall Project

As enterprise information systems are collecting event streams from various sources, the ability of a system to automatically detect anomalous events and further provide human readable explanations is of paramount importance. In the EXAD project, we develop an “Explainable Anomaly Detection” framework that harnesses the power of latest machine learning techniques for anomaly detection while being able to return human-readable explanations for interpreting prediction results, thereby increasing the trust of model predictions and providing valuable, actionable information to enterprise users. To do so, our system employs a range of novel techniques, including new human-interpretable dimensionality reduction methods, fast explanation discovery methods, and a new benchmark for comparing various anomaly detection and explanation discovery methods in real-world use cases.

The postdoc is expected to further extend the EXAD system, in particular, to develop a benchmark in the new area of financial data analysis, and to develop new data encoding schemes, as well as improved explainable anomaly detection methods, for this new domain.

The postdoc will find an active and collaborative environment at Ecole polytechnique, with world-renowned researchers in data analytics systems, data mining, machine learning, and statistics. Ecole Polytechnique is a French public institution of higher education and research, located in Palaiseau 45 minutes southwest of Paris. It is considered the most prestigious engineering school in France, with well-known educational programs in science and engineering. Among its alumni are three Nobel prize winners, one Fields Medalist, three Presidents of France, and many CEOs of French and international companies.

  1. Skills Required from the Applicant
  • A PhD degree in areas related to data science, big data analytics, and data stream analytics.

  • Knowledge of recent machine learning techniques for anomaly detection or related statistical data analytics, as well as data management systems, is preferred.

  • The application is also expected to have strong programming experience in Python and related machine learning libraries.

  1. Application

The position is available immediately. Application is open until the position is filled. The interested applicant is asked to submit a resume and 2 names of references to Prof. Yanlei Diao ( and Ms. Jessica Gameiro (