All positions are in the Machine Learning subgroup of the Section for Declarative Languages and Artificial Intelligence (DTAI), 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 five faculty members ( Hendrik Blockeel, Jesse Davis, Luc De Raedt, Tias Guns, Angelika Kimmig), one Fellow of KU Leuven’s Industrial Research Fund (Wannes Meert), about 10 post-docs and over 30 doctoral students. The Machine Learning group follows an artificial intelligence approach to the analysis of data. It investigates a wide variety of machine learning and data science problems. It mostly concentrates on problems that involve complex and structured data and background knowledge. It has expertise in areas such as Learning and Reasoning, Automated Data Science, Learning Constraints and Optimisation Criteria, (Constrained) Clustering, Probabilistic Programming, Statistical Relational Artificial Intelligence, Probabilistic Graphical Models, Neural Symbolic Computation, 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). The lab is hiring 1) 2 PhD students working with Prof. Tias Guns on the combination of machine learning techniques (preference learning, learning to rank and explainable AI) and constraint solving (CP/SAT/MIP), to learn and explain user preferences in problems such as vehicle routing, timetabling, scheduling etc. (see https://people.cs.kuleuven.be/~tias.guns/chat-opt.html) 2) 2-3 PhD students working with Prof. Jesse Davis on the topics of automating data science (e.g., automated feature construction) and positive and unlabeled learning (see: https://dtai.cs.kuleuven.be/drupal/projects/na-1), 3) 1 student working with Prof. Angelika Kimmig on automatically learning probabilistic logic programs. Probabilistic programs are well-suited for reasoning and decision making in complex, uncertain domains but encoding them manually is cumbersome (see https://www.kuleuven.be/onderzoek/portaal/#/projecten/3E201127?hl=en&lang=en), 4) 1 student working with Prof. Hendrik Blockeel on incorporating knowledge in the form of constraints in the process of learning and evaluating models. Such constraints can make the learning process more efficient, the learned models safer / fairer / more accurate, and the evaluation methods more reliable. (https://dtai.cs.kuleuven.be/drupal/projects/verilearn). 5) 2 students working with Prof. Luc De Raedt on statistical relational learning and neural symbolic methods for learning and reasoning about dynamics and for automating data science, see (https://dtai.cs.kuleuven.be/drupal/projects/na-5 and https://dtai.cs.kuleuven.be/drupal/projects/nplp). Expertise in one or more of these areas is welcomed. Website unit
You will work under the supervision of and be mentored by one of the professors of the Machine Learning group, that is, Profs. Hendrik Blockeel, Jesse Davis, Luc De Raedt, Tias Guns or Angelika Kimmig. You will be part of a dynamic team that performs cutting-edge research in artificial intelligence, machine learning and data science. You will play an active role in the research team, publish papers, take part in workshops, public events and other activities.
The candidates should have a Master’s degree in Computer Science or Artificial Intelligence.
Candidates must have excellent theoretical and programming skills, be proficient in oral and written English, possess excellent communication skills, multi-tasking skills, and be team-oriented, proactive and result driven. The positions can start immediately, and positions will be filled as soon as suitable candidates are found. Interested candidates should send their résumé, contact information of 2 or 3 referees, and a motivation letter using the KU Leuven system. The motivation letter should clearly identify the topic(s) the candidate wants to work on, it should clearly specify the reasons for these choices, as well as possible past experience in the area.
A PhD position, initially for one year, but extendible until max. 4 years.
A stimulating environment at a European top university in a well-equipped, experienced and internationally oriented research unit.
The research will be based at the Department of Computer Science at the Arenberg Campus in Heverlee (close to the center of Leuven).
For more information please contact the responsible professor for the topic you are most interested in, i.e. Profs. Hendrik Blockeel, Jesse Davis, Luc De Raedt, Tias Guns or Angelika Kimmig at firstname.lastname@example.org. You can apply for this job no later than September 01, 2021 via the online application toolKU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.