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conversational guides for enhancing visitors’ learning and experiences in public educational environments. The PhD student will focus on addressing the challenge of visual blindness in large language models (LLMs
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found in the areas of: Human-Technology Interaction Form and Function Modeling and Simulation Product Development Material Production and in the interaction between these areas. The research covers
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plasma model (www.amitiscode.com ). By comparing model results with NASA’s MESSENGER and ESA’s/JAXA’s BepiColombo observations, the research aims to deepen our understanding of Mercury’s magnetosphere
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in humans and in animal models. Environmental factors have been reported to predict the risks of developing SUDs too. For instance, epidemiological data have shown that impoverished social environments
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in Python programming. Experience with machine learning methods, bioinformatics, and data science. Familiarity with generative AI tools for protein design and protein language models. Knowledge
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interfaces and driver modelling Implementation of control algorithms in mechatronic systems Experimental design and statistical methods Vehicle testing and test methods involving human test subjects What you
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of this WASP-financed project is machine learning, in particular dealing with generative models and instabilities associated with cycles of retraining on mixtures of human and machine-generated data
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components in time and space, from single molecules to native tissue environments. The project The industrial PhD student will develop AI and machine learning models to predict drug metabolism, a critical area
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-technology/ Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Sustainability assessment and biophysical modelling Research subject: Technology
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, flexible and adaptable distributed system of systems. Example of specific problems are: -Information interoperability supported by ontologies. -Unified data models for operational environmental impact -SOA