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Associate Data Scientist participates in biomedical research projects using programming, data -mining, statistics, machine learning, and visualization techniques to assist with the development, evaluation
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learning and development Proficient in technical writing and presentation Possess strong analytical and critical thinking skills Show strong initiative and take ownership of work Where to apply Website https
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- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute to a corpus of geo-analytical scenarios with
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reporting. Understand how data flows through EDW, ODS, and data marts. Learn fundamentals of dimensional modeling and data lineage. Develop precision, documentation habits, and professional communication
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well as predictive models based on machine-learning technologies, in order to carry out code development and testing activities within the listed projects; therefore, skills in software design and development
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, or machine learning models). Experience with high-performance computing and version control (e.g., GitHub). History of large-scale project implementation work in an international setting (e.g, population
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at the interface of machine learning, statistics, and live-cell biology. The position is co-supervised by Prof. Olivier Pertz (Cell Biology) and Prof. David Ginsbourger (Statistics), and the student will be equally
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As a component of the faculty cluster initiative, the Chancellor’s Faculty Excellence Program , NC State University is recruiting one tenure track Assistant Professor in mathematical modeling/machine
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of physics- informed machine learning and deep learning, with applications to inverse problems in scientific imaging and the modeling of complex physical systems. The overall goal is to integrate the knowledge
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intelligence, robotics, machine learning, and human-robot interaction. Project Description The focus of the project is artificial intelligence (AI) and specifically the use of large language models in health