Sort by
Refine Your Search
-
renewable energy generation.KU Leuven leads Modelling and Optimization, which focuses on: Developing hybrid models combining first-principle and machine learning approaches. Creating predictive frameworks
-
for the bachelor and master programs a deep interest in and excellent knowledge of critical studies of the labour ecology nexus as well as agricultural policy. knowledge in qualitative and quantitative empirical
-
you to apply. The opportunity to work on a challenging and advanced research topic, in a dynamic academic environment, to acquire research and project management skills, to network with leading
-
) inconsortium/institutional seminars and national/international symposiums or conferences. Eager to carry out visitations (if required) to other laboratories (within Belgium or abroad) for learning new techniques
-
diverse, international, and multidisciplinary research team • Opportunities to collaborate with scholars of different levels and with communities in six countries • We also offer a supportive learning
-
knowledge of Microsoft Word, Excel and PowerPoint. You have experience in, or are willing to learn MATLAB. You hold the FELASA B certificate, or international equivalent or you are willing to follow a
-
international workshops and conferences, presenting and discussing your research globally. Teach and contribute: Provide support for teaching activities and teaching innovation. Build up and apply skills: Build
-
are eager to learn, you are able to reflect on your own approach to work and you welcome feedback as an opportunity for development- You are engaged at work, but you are also able to easily disconnect
-
neuromorphic ultra-low-power active sensor readout and processing at the edge. The chip design will enable online learning capabilities, aiming at modulating the spatio-temporal filtering properties with
-
off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception