MACHINE LEARNING FOR REAL-TIME DATA PROCESSING IN LIMITING CIRCUMSTANCES
In the Science, Engineering and Technology Group, Faculty of Engineering Technology, Department of Computer Science, Technology Campus Geel at KU Leuven, there is a full-time academic vacancy (part of the senior academic staff) in the area of Machine Learning. We are looking for internationally orientated candidates with an excellent research file and with educational competencies within the field of Machine Learning, as seen from a computer science point of view, i.e., with a focus an algorithmic aspects, computational efficiency and aspects of knowledge representation. Attention should be paid to applications within computer science. The research on Machine Learning and Statistics at Technology Campus Geel is embedded in the Technology Cluster Computer Science of the Department of Computer Science. The Technology Cluster Computer Science focuses mainly on demand-driven research, often in collaboration with industry and other organisations. Together with the Computer Science part of the EAVISE group at Technology Campus De Nayer, this research group is affiliated with the internationally renowned research group DTAI (Declarative Languages and Artificial Intelligence).
The teaching activities are situated in the Faculty of Engineering Technology, which has developed a unique multi-campus model spread over seven campuses in Flanders. Both education and research activities are mainly coupled to KU Leuven, Technology campus Geel.
You develop a research programme at KU Leuven, Technology Campus Geel in the domain Machine Learning focussing on applied research. You collaborate with other research groups at KU Leuven and other universities. You provide additional expertise, thereby strengthening the fundamental research, and you identify topics within existing research programmes that are relevant for your own research, thereby providing your own research with a fundamental basis. Examples of possible research programmes are:
- research into classification models that can be applied in real-time to various kinds of sensor data, and learning algorithms for such models; here, limitations may exist in terms of computation power, memory, or energy usage, especially in the real-time component;
- research into adaptive models that can be trained for use in specific circumstances with limited supervision;
- learning causal models for industrial processes, that allow the cause of a defect to be automatically determined;
- developing systems for big data analysis in specific sectors or application domains, by applying expertise on generally applicable fundamental results, algorithms and methods.
You develop a network, both within the academic and non-academic world, to strengthen the collaboration between both, among others for the valorisation of scientific results. You are able to acquire competitive funding, both project-based government funding as well as industrial funding.
Opportunities exist for collaboration with, among others:
- research groups at Technology Campus Geel: `electronics for harsh environments', `sustainable food production including supporting mechatronic systems' and `sustainable thermal energy',
- EAVISE, Technology Campus De Nayer: `Artificial Intelligence and Computer Vision',
- Research group DTAI of the Department of Computer Science, focused mainly on fundamental AI research.
You provide high-quality education at Technology Campus Geel, in the Faculty of Engineering Technology, mainly in the bachelor and master programme Electronics-ICT, in the domain of computer science/information technology. You teach the subjects `Programmin...
This job comes from a partnership with Science Magazine and