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slowly, or act quickly but lack robust planning. Frontier models typically depend on heavy compute, cloud inference or controlled settings, limiting real-world use under compute, latency and energy
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and sustainability; Investigate and apply artificial intelligence and machine learning techniques, including large language models (LLMs), across CENSE’s scientific body in its five thematic areas
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(USBE) is recruiting one to two PhD students in Statistics for the research project “Next-Generation Latent Variable Models for Social Data Science”. Application deadline: November 4, 2026. We
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to Specific Requirements Experience in inflammatory bowel disease, immunology, inflammation,biomarkers, or related fields. Experience with cell cultures, organoids, or other experimental models. Knowledge
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– Robustness of dehydration detection: Examine the consistency of saliva-based dehydration detection across different dehydration models and participant cohorts, including sport and occupational settings
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of granular heating and fragmentation, and feed the results into a new depth-averaged model of debris-avalanche dynamics. Your work will directly improve the physical models used to forecast the behaviour
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in auditory neuroscience, neuroimaging, and AI/NeuroAI. In this role you will bridge human neuroimaging and computational modelling . You will collect and analyse neuroimaging data (7 Tesla fMRI
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of: electromagnetic sensor design, modelling, prototyping and experimental validation. The best fit is A candidate interested in high-frequency measurement techniques, sensor hardware development and precision
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collaboration with internal and external partners, predictive models including machine learning (ML), materials thermodynamics, etc. for high-throughput identification and screening of advanced materials for gas
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the Job related to staff position within a Research Infrastructure? No Offer Description PhD position: Improving Language Models with Formal Knowledge in Industry. Details: https://www.science.hr/jobs