Sort by
Refine Your Search
-
The successful candidate will join the CritiX research group (https://www.uni.lu/snt-en/research-groups/CRITIX/ ) headed by Prof. Marcus Völp. The team focuses on critical information
-
research focused on biomedical image computing. Our work involves developing state-of-the-art methods for image segmentation, detection, classification, predictive modelling, and image enhancement. We aim
-
will pursue a Ph.D. degree (Doctorate) in computer science or software engineering with a focus on differential privacy (DP) and other secure computing techniques while collaborating with the Ministry
-
computational models and data analysis code to process large, multimodal behavioral datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning
-
backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
-
-based numerical and statistical tools Language skills • Fluency in English, both oral and written. Skills in French is an asset. Your LIST benefits · An organization with a passion for impact and
-
You will join the recently established Chemical and Molecular Neurobiology group led by Associate Prof. Ivana Nikić-Spiegel at the LCSB. Our research combines innovative approaches in protein
-
LVLMs for autonomous driving. Objectives Design, develop, and evaluate novel method(s) to detect and localize hallucinations in LVLM outputs for autonomous driving tasks Investigate and propose mitigation
-
related discipline • Some knowledge of the theory of materials and experience with computational methods in materials science • Some experience with machine-learning interatomic potentials • Good
-
SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
materials science or a related discipline • Some knowledge of the theory of materials and experience with computational methods in materials science • Some experience with machine-learning interatomic