33 machine-learning "https:" "https:" "https:" "https:" "https:" positions in Luxembourg
Sort by
Refine Your Search
-
and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
-
Mathematics, or a related field A strong background in image/signal processing, particularly in computer vision. Strong programming skills and experience with at least one deep learning framework e.g
-
Mathematics, or a related field A strong background in image/signal processing, particularly in computer vision. Strong programming skills and experience with at least one deep learning framework e.g
-
-performance computing resources suitable for large-scale machine-learning and foundation-model experiments. Your role We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025
-
use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
-
use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
-
/performance trade-offs and typical RAN levers; experience with energy metering data is a plus. • Strong background in AI / Machine Learning for decision-making (e.g., forecasting, optimization with learning
-
3GPP compliant 5G/6G NR NTN OFDM waveforms Develop and analyse signal processing and/or machine learning algorithms for joint channel, delay, Doppler and carrier phase estimation, remote object ranging
-
understand, explain and advance society and environment we live in. Your role The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs
-
if they demonstrate strong relevant skills. Coursework or strong background in computational mechanics / FEM, numerical methods, and scientific programming. Exposure to machine learning / data-driven modelling and/or