Postdoctoral position: Machine Learning, Anomaly Detection and Machine Monitorin

KU Leuven
August 22 2017
Position Type
Full Time
Organization Type

A postdoctoral position is available in the area of Machine Learning, Anomaly Detection, and Machine Monitoring with a strong focus on applications on real-world use cases. The position is in the DTAI research group, part of the Department of Computer Science at KU Leuven. You will work with Prof. Jesse Davis and Dr. Wannes Meert. The research group focusses especially on applications involving Probabilistic Programming, Statistical Relational Artificial Intelligence, Probabilistic Graphical Models, (Constrained) Clustering, Anomaly Detection and Sensor data. The candidate will focus on developing and adapting machine learning techniques to use cases offered by our industrial partners, and setting up proof-of-concept systems to validate the results. This mainly in the scope of the VLAIO-SBO project "Hypermodelling strategies on multi-stream time-series data for operational optimization". You will also interact with the Sports Analytics Group that Prof. Davis directs. The lab for Declarative Languages and Artificial Intelligence (DTAI) is one of the leading research groups for machine learning and data mining. DTAI's machine learning group counts four faculty members (Luc De Raedt, Hendrik Blockeel, Bettina Berendt and Jesse Davis), one research manager, one research expert, around 5 post-docs and over 25 doctoral students.

DTAI is internationally renowned for its expertise in integrating different forms of reasoning (inductive, deductive and probabilistic), in logical learning, statistical relational learning, probabilistic programming, learning from structured data (relational databases and graphs), inductive logic programming, inductive databases, action-activity learning, knowledge representation, data mining, and constraint programming.

Next to fundamental research in machine learning and data mining, the DTAI group applies the developed techniques to concrete cases situated in intensive care monitoring, predictive maintenance, smart self-diagnosis, mechatronics, robot manipulation and navigation, bio- and chem-informatics, natural language processing, smart electronics, computer vision, etc. For these applications, DTAI cooperates with other groups from strategically chosen research areas.

You will work under the supervision of Prof. Jesse Davis and Dr. Wannes Meert. You will be part of the team that connects the basic machine learning research and the applications. You will play an active role in this research team, publish papers on application of machine learning, take part in workshops, public events and other activities.

This job comes from a partnership with Science Magazine and Euraxess

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