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for the position. Curriculum Vitae (CV). List of publications. Copies of PhD diploma and other relevant degrees. Contact information for two references. Applications should be written in Swedish or English and
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between the two linked studies as well as taking the lead in the large-scale qualitative secondary analysis of interview data from multiple sources. In this role you will be expected to contribute
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and application of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal candidate will have recently completed (or be close to completing) a PhD in
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research. Your position Design, implement, and evaluate large-language-model (LLM) pipelines for synthetic data (fine-tuning, retrieval-augmented generation [RAG], prompt engineering). Plan and analyze
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environment for all employees through mutual respect and tolerance. Description of the project The postdoc will leverage existing high-throughput data from large scale cohorts and large family cohorts
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 15 days ago
to contribute to innovative projects at the forefront of healthcare delivery improvement, leveraging Large Language Models (LLMs) and clinical data analysis. About the Position Our Postdoctoral Research Program
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The postdoctoral researcher will work with computer-based analytical methods and large databases to develop theory and methodology for utilising aggregated data from archaeology, genetics, and linguistics, thereby
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engineering practices for machine learning Tabular machine learning Large language models on structured and semi-structured data Research Associate Role: Under the direction of their supervisor, the candidate
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: Strong programming skills, a valid driving license, and experience with large-scale 3D MT data acquisition, processing and inversion are essential. Experience in driving snowmobile and strong publication
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We invite applications for a Postdoctoral Researcher to join the research group of Professor Christopher Yau ( http://cwcyau.github.io ) at the Big Data Institute, University of Oxford. This post