Several Post-Doc Positions in Machine Learning and Artificial Intelligence

All positions are in the Machine Learning subgroup of the Lab for Declarative Languages and Artificial Intelligence, part of the Department of Computer Science at KU Leuven. The DTAI lab is one of the leading research groups for machine learning, artificial intelligence and data mining. DTAI’s machine learning group currently counts four faculty members (Luc De Raedt, Hendrik Blockeel, Bettina Berendt and Jesse Davis), one research manager, one research expert, several post-docs and over 25 doctoral students.

The Machine Learning group follows an artificial intelligence approach to the analysis of data. It investigates a wide variety of machine learning, data mining and data analysis problems. It mostly concentrates on problems that involve complex and structured data and background knowledge. It has expertise in areas such as Logic and Learning, Probabilistic Programming, Statistical Relational Artificial Intelligence, Probabilistic Graphical Models, Automated Data Science, Learning Constraints and Optimisation Criteria, (Constrained) Clustering, Predictive Learning, Verification and Machine Learning and it is applying its expertise in areas such as Anomaly Detection, Sports Analytics, Robotics, Sensor data, Action and Activity Learning and Operations Research (see https://dtai.cs.kuleuven.be/ for more information). It is also investigating privacy, safety and other ethical issues in data science and artificial intelligence.

The lab is hiring post-docs in the areas of

1. automated data science, cf. the ERC AdG project SYNTH (see https://synth.cs.kuleuven.be/);
2. the verification of software involving artificial intelligence and machine learning components, cf. the Excelllence of Science project Verilearn (see https://dtai.cs.kuleuven.be/projects/verilearn); and
3. probabilistic programming and statistical relational learning for action- and activity learning, planning, and cognitive robotics.

Expertise in one or more of the following areas of artificial intelligence and machine learning is essential: automated machine learning and data science, probabilistic programming, Markov decision processes and reinforcement learning, probabilistic planning, cognitive robotics, statistical relational artificial intelligence.

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