Sort by
Refine Your Search
-
Listed
-
Employer
- Leiden University
- Delft University of Technology
- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); today published
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); Eindhoven
- Erasmus University Rotterdam
- KNAW
- Leiden University; today published
- University of Groningen
- University of Twente
- University of Twente (UT)
- University of Twente (UT); Enschede
- Utrecht University
- Wageningen University and Research Center
- Wetsus - European centre of excellence for sustainable water technology
- 6 more »
- « less
-
Field
-
for a: PhD Candidate in Emotionally and Socially Aware Natural Language Processing (1.0fte) Project description Current Natural Language Processing (NLP) systems, and especially large language models
-
description Current Natural Language Processing (NLP) systems, and especially large language models (LLMs), are interacting with human emotions more readily than earlier AI systems, but we still lack frameworks
-
) Project description Current Natural Language Processing (NLP) systems, and especially large language models (LLMs), are interacting with human emotions more readily than earlier AI systems, but we still
-
children with autism and eating behavior challenges. This research explores how large language models (LLMs), interactive robotics, and multimodal technologies can support creative expression and
-
will be to: identify policy mechanisms that can change infrastructure affordance and lower infrastructure use develop an agent-based model that regards infrastructure as a socio-technical system reveal
-
that the developed methods are robust, adaptable, and grounded in real-world practice. You will apply advanced techniques such as agent-based modelling, quantitative resilience assessment, and risk analysis to
-
-based modelling, quantitative resilience assessment, and risk analysis to simulate and optimise resilience strategies. The framework will be tested and refined through pilot studies in collaboration with
-
combine engineering design principles with stake-holder engagement tools to support decision-making under uncertainty. Using methods like agent-based modelling, quantitative resilience and risk analysis
-
children with autism and eating behavior challenges. This research explores how large language models (LLMs), interactive robotics, and multimodal technologies can support creative expression and
-
operational performance. Based on feedwater composition (salinity, monovalent/divalent ion ratios, and valuable elements), you will model and design ED configurations that produce tailored concentrate streams