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will design and implement differential privacy solutions for large-scale scientific data models in federated learning environments. You will advance privacy-preserving machine learning by developing
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optimization of large language models (LLMs) and related architectures for generative tasks, continuous learning, indexing or retrieval, support of retrieval augmented generation over many data points from long
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motivated Postdoctoral Research Fellow to develop and apply innovative, data-driven models for seismology, with a focus on developing cutting-edge foundation models. This is an exceptional opportunity
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. The project explores novel communication, sensing, and data-driven techniques to support safer and more adaptive interactions among heterogeneous road users. The research will be carried out under
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Qualifications:. PhD in one of these fields: Computer Science, Data Science, Biomedical Informatics, Computational Biology, Information Science or a related field. Experience in at least one of the following
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4 Sep 2026 Job Information Organisation/Company Uppsala universitet Department Uppsala University, Disciplinary Domain of Science and Technology, Faculty of Chemistry, Department of Chemistry
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such as breakwaters by using computational tools developed in our research group. These tools are based on discrete element method and they have bee validated against experimental data. You will start your
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Research Associate will design and perform infection and time-course experiments, generate and analyze host and bacterial transcriptomic data, and integrate phenotypic outcomes with differential gene
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Job Description Here's a Glimpse of the Job The Postdoctoral Research Associate will be involved in developing deep learning architecture for multi-object data integration, federated learning approaches
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the supervision of Dr Ruiz-Castell, the Postdoctoral Fellow will contribute to data processing and analysis on ongoing and developing environmental health/exposome projects and will co-develop a competitive grant