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and machine learning models. To be successful in this role, you will have excellent communication skills and written English, strong quantitative and analytical skills, the ability to work creatively
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) to integrate advanced AI/ML techniques into the RWE generation pipeline. Requirements PhD degree in Epidemiology, Data Science, Statistics, Computer Science, Informatics or related disciplines. Preferably
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Data Scientist (Artificial Intelligence). We now invite applications for the captioned post. Duties and Responsibilities Develop and apply advanced artificial intelligence and machine learning models
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) signal processing, machine/deep-learning and computational linguistics. The team mobilizes them to produce methodologically sound research in response to some of the challenges posed by the nature and
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. You have: A PhD in Computer Science, Machine Learning, Applied Mathematics, Scientific Computing, Data Engineering, or a closely related field. Demonstrated ability to conduct high-quality academic
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–functional modeling of root system architecture. Phenomics data integration and high-dimensional trait analysis. Predictive breeding and quantitative genetic modeling. Machine learning approaches to genotype
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senior research position to work on projects related to computational analysis of mass spectrometric datasets. A major focus will be on the application of AI/machine learning models and other computational
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developing cutting-edge active-learning (Bayesian optimisation) methods that integrate chemical knowledge by capitalising on Large Language Models (LLMs) as well as human knowledge. You should have a PhD in
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work is studying how undergraduate STEM courses can be tailored to meet the needs of all learners. Current projects involve studying STEM instructor perceptions of student-centered learning as
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, measure transport and machine learning on developing a novel mathematical framework for identifying reduced dynamical models of high-dimensional complex multi-scale systems. The project will develop fast