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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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ExperienceNone Additional Information Eligibility criteria **Technical and Scientific Skills** PhD in analytical chemistry, biogeochemistry, environmental sciences, or a related discipline. Strong experience in
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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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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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PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, or a related quantitative field * Demonstrated expertise in programming and scripting (e.g. R, Python, Bash) for data
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postdoctoral associate positions, starting immediately. Dr. Liu has extensive experience in big data analytics, systems biology, probabilistic graphical models, causal inference and machine learning. Dr. Liu's
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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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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 22 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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that automatically choose and adapt encodings, and integrating these capabilities into a user-friendly framework that empowers mathematicians to pose, explore, and resolve large combinatorial problems with SAT
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leverage existing high-throughput data from large scale cohorts and large family cohorts complemented with bulk and single cell RNAseq data from relevant tissues to investigate T2D pathogenesis and its early