35 machine-learning positions at Ghent University

Postdoctoral fellow - Department of Environment

languages, such as, MATLAB Toolbox, LabVIEW, DaisyLab, AutoCAD, C++….. Advanced knowledge in sensing technologies and measurement systems. Advanced knowledge in machine learning, deep learning and data fusion

PhD Student - Department of Electronics and Information Systems

computer power. Depending on the interest of the candidate, the student will work on one of the following topics: Developing new methods for simulations of drug transport through cell membranes, building up

PhD student

such computational methodologies exist, new fundamental developments are needed to understand the ‘time’ aspects and to make the computations feasible with present-day computer power. Depending on the interest

PhD Student

fields, Ghent University is a logical choice for its staff and students. The IDLab Ghent research group is seeking a highly motivated and talented PhD student to join the distributed machine learning team

PhD Student

of the larger research groups at imec. Our major research areas are machine learning and data mining; semantic intelligence; multimedia processing; distributed intelligence for IoT; cloud and big data

PhD Student

machine learning team. Our team focuses on developing efficient machine learning algorithms for perception and control; with diverse applications in industry, robotics, remote sensing and agriculture. As

Doctoral fellow

Job description To perform research on machine learning applied to the understanding and prediction of extreme hydroclimatic events. Job profile Researchers must hold an MSc in domains related

PhD Student

domains of clinical neurophysiology. Knowledge in the field of artificial intelligence deep learning and machine learning is highly appreciated. The candidate should be a collaborative, dynamic person who

PhD Student

of mathematical modelling, data analysis and machine learning or a strong affinity to learn Background in semantic data models is a plus Knowledge in modelling and integrated assessment of water and wastewater

PhD Student

theoretical and computer modelling. A performant model will allow a more realistic simulation of electrophoretic systems, widening our understanding of the phenomena and enabling the improvement of current