Automating Data Science (ERC) / Probabilistic Programming / Relational Learning
In the Machine Learning group, our researchers investigate a wide variety of machine learning, data mining and data analysis problems from an artificial intelligence perspective. They concentrate on problems that involve complex and structured data and background knowledge using expressive relational representations, rich probabilistic models, graphs and networks.
There are several openings for PhD students working under Prof. Luc De Raedt in the following projects:
- the ERC Advanced GrantSYNTH (Synthesising Inductive Data Models) which started on September 1, 2016.The ultimate goal of the SYNTH project is to automate data science, in particular the role of the data scientist when developing intelligent systems, which is to extract knowledge from data in the form of models. SYNTH wants to develop the foundations of a theory and methodology for automatically synthesising inductive data models using artificial intelligence, data mining, machine learning and probabilistic methods; see https://dtai.cs.kuleuven.be/projects/synth for more details;
- FWO projects related to probabilistic programming, relational learning and their applications in robotics; here the goal is to develop fast methods for inference in probabilistic programming and databases; such programming and database languages allow to express uncertainty using artificial intelligence techniques, and the underlying models can also be learned from data; see https://dtai.cs.kuleuven.be/projects/reground and https://dtai.cs.kuleuven.be/projects/accinfprobdb for more information.
The ideal candidate is a computer scientist with interests and expertise in artificial intelligence, databases, data mining, machine learning, and/or probabilistic graphical models. He/She is interested in theory, a skilled programmer, and excited about applications of AI and data science. He/She is dynamic and open-minded.
Post-docs should have experience with at least one of the following domains : probabilistic programming, graphical models, constraint programming, pattern mining or (statistical) relational learning.
- A full time PhD scholarship of 1 year, extendible until max. 4 years, or alternatively a post-doc position.
- A dynamic, international environment at the lab for Declarative Languages and Artificial Intelligence.
- KU Leuven is equal opportunity employer.
Positions will be filled as soon as suitable candidates are found. You can apply for this job no later than November 30, 2016 via the online application tool.
While applying for the job please refer to jobvector and use the following reference number: BAP-2016-441
About KU Leuven
KU Leuven is an ambitious, international and research-oriented university. Internally, the university tries to maintain a balance between the power of the big ship and the flotilla of small, mobile, independent vessels of which it is composed. KU Leuven is home to a lot of creative, young and academic talent. As a leading university in Europe, it is looking for staff who can think outside the box.More about KU Leuven