Sort by
Refine Your Search
-
be placed on Representation Learning techniques, Transformer-based architectures, Large Language Models (LLMs), Natural Language Processing (NLP), etc. The research will also explore distributed data
-
practices. The findings will serve as the empirical foundation for the security framework. Defensive Strategies: Propose and prototype new defensive architectures and techniques that can be integrated
-
highly motivated and self-driven geoscientist that can enrich and strengthen the Department in subjects related to alluvial fan sedimentology, architecture, and petrography. The position will focus
-
structured around two main pillars: Network resilience and sovereignty, i.e., research on networking architectures and mechanisms that keep critical networks and applications they support running optimally
-
the Department in subjects related to alluvial fan sedimentology, architecture, and petrography. The position will focus on developing new concepts in catchment–alluvial fan dynamics within a structural framework
-
information, and case files Potential research topics for the Ph.D. project are: Adaptation of language model architectures and pipelines for high-stakes public sector Benchmark and comparative analysis methods
-
multimodal data, dynamic updates, and scalable semantic interoperability in large-scale DPP systems. Particular emphasis will be placed on Representation Learning techniques, Transformer-based architectures
-
scalable semantic interoperability in large-scale DPP systems. Particular emphasis will be placed on Representation Learning techniques, Transformer-based architectures, Large Language Models (LLMs), Natural
-
. The planned PhD research topic will explore techniques to handle protected data in digital twin architectures. To explore and investigate this topic, the project will combine formal methods, programming