Sort by
Refine Your Search
-
actively shape interdisciplinary theory on sustainable transformations and well-being. The successful candidate will join the Institute for Lifespan Development, Family and Culture within the Department
-
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
-
research, work in a highly supportive and international environment, and actively shape interdisciplinary theory on sustainable transformations and well-being. The successful candidate will join the
-
systems Reinforcement Learning and Agentic Control: Hands-on experience with reinforcement learning, multi-agent systems, or planning-based agents for autonomous vehicles or robots operating in dynamic
-
and www.spacer.lu The candidate should develop the following tasks: Conduct cutting-edge research in learning-based and/or model-based control and/or perception strategies for dexterous robotic
-
procedures Innovative teaching experience and interest to develop these further Fluency in English is required; good command of French, Luxembourgish and / or German is considered an asset We offer
-
Biology, Data Science, or a related field. Technical Proficiency: Strong command of R. Knowledge of Python is an asset. Multi-Omics Expertise: Proven experience in the analysis and integration of diverse
-
targets. Key Responsibilities: Perform deep immunophenotyping of CD8 T cell subsets in cohorts of RBD participants and healthy controls Screen for autoantibodies using genome-scale protein microarrays and
-
control) using real operator-grade datasets (traffic indicators, network KPI's, configuration logs and energy measurements when available). • Investigating and combining multiple energy-saving levers (e.g