Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
potential of these measurements, there is a strong need of developing AI algorithms able to do real-time analyses of such data. Your immediate leader will be the Group leader of Manufacturing Engineering at
-
to leverage on the fast-developing expertise in multi-disciplinary forest research in Luxembourg, LIST, in collaboration with the University of Luxembourg and the Luxembourg Institute of Socio-Economic
-
Description We are looking for a PhD-candidate interested in topics that lie on the border of optimization by the use of heuristic algorithms and (Explainable) Artificial Intelligence ((X)AI). Specifically, in
-
new generation of perceptual foundation models by contributing advanced perceptual pre-training and fine-tuning algorithms. What you will do You will carry out research and development in the areas
-
-tuning algorithms. What you will do You will carry out research and development in the areas of perceptual foundation models, using advances in deep machine learning and computer vision. The goal is to
-
) programme. The network brings together 17 academic and industrial partners across Europe with the goal of developing novel approaches to the modelling and control of flexible structures. This programme will
-
simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power consumption and
-
(https://metaproteomics.org/ ) formed a strategic alliance to set up a powerful and interdisciplinary network called METAMIC to capitalize on the potential of metaproteomics for developing novel strategies
-
will join an international and multidisciplinary team and will work in the project which aims to develop an innovative, modular, and partially bioresorbable wound filler for Negative Pressure Wound
-
these frameworks to develop specific formulations and solution algorithms for the design of congestion pricing schemes using classical transport models and quantify the equity-efficiency trade-offs for congestion