48 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"SUNY" uni jobs in Belgium
Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
proven practical experience in the implementation of machine vision systems Fluent in English, for both written and oral communication Enthusiastic team player Openness to learn the basics of plant growth
-
research and development in Swarm Intelligence and Machine Learning, addressing challenges in counter drone swarm formation and defense Design, develop and conduct experiments of drone swarms using both
-
citation record must be focused on AI; or alternatively (B), machine learning engineers with an AI-focused PhD and demonstrated 2-year industry experience in AI development Applicants must have in-depth
-
the lifecycle of industrial systems. As machine learning sees broader adoption, companies are increasingly required to ensure the safety of machine-learning-enabled systems. The reliance on training data and the
-
. ETRO, the Department of Electronics and Informatics (http://www.etrovub.be/) of the Vrije Universiteit Brussel (VUB), performs fundamental and applied research in signal processing, AI, computer vision
-
how a novel machine learning-based methodology leveraging reinforcement learning with human feedback and multi-objective optimisation can be realized to generate new and even improve existing work plans
-
within the CVAMO Flanders Make Lab at Ghent University. The project focuses on developing machine learning models to predict manufacturability and manufacturing effort directly from CAD geometry
-
European cities. The project explicitly embraces a broad AI perspective, including (but not limited to): machine learning and statistical learning computer vision and sensor-based data analysis natural
-
, collaborative science Experience with tools for qualitative and quantitative analysis; experience and practice with machine learning and Artificial Intelligence are also considered assets Language requirements
-
, incorporating transient tribological changes. Creating machine-learning-based surrogate models to enable rapid efficiency and lifetime predictions under realistic operating conditions. Validating the developed