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Qualifications: PhD or equivalent in public health, health policy, health services research, data science, epidemiology or a related field. Strong data analytic skills, including experience with SAS and/or R
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datasets, such as large-scale data, text as data, or satellite imagery (‘Big Data Economics’). The ifo Institute is one of Europe’s leading economic research institutes. Research at ifo combines academic
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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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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 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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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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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
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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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media data using platform APIs and/or web scraping Analyse large-scale data using appropriate digital methods (flexible, but please specify) Present research at national and/or international events Lead
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experiment and data modeling approaches. Required qualifications PhD in molecular biology, biotechnology, bioengineering, bioinformatics, chemistry or related fields. 3+ years hands on experience with high
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(Shannon entropy, compressibility, effective complexity and logical depth). The data basis for the analyses are two-fold: first, recent connectome data, i. e. large datasets of all synaptic connections in