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of Chicago Law School. Responsibilities will span all stages of research, including collecting data of in both tabular and spatial formats, developing algorithms that clean and organize data, conducting
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, statistical applications, programming, analysis and modeling. The Ovarian Cancer Research Lab at the University of Chicago is seeking a full-time, on-site Clinical Data Scientist/Analyst to support multiple
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responsibilities will span all stages of research, including collecting data of in both tabular and spatial formats, developing algorithms that clean and organize data, conducting statistical analyses, running
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foundations and applications of large language models (LLMs) or the development of novel AI algorithms utilizing the latest technologies for applications in science and technology. The successful candidate will
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experience and plans lie at the forefront of areas such as quantum computing, quantum algorithms, quantum simulations, and quantum error correction. Predominant research activities of the selected candidate
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modeling, machine learning algorithms, and decision support tools focused on atmospheric, land-surface, and hydrologic conditions related to extreme weather events and their impacts. CW3E is an interface
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progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and
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position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate
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of structures, facilitating a form-finding process driven by FEM analysis. Training deep learning algorithms to suggest multiple structural concepts tailored to specific boundary conditions. Expanding FEM
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to support local people and communities everywhere. By working in and across multiple scientific areas, CALS can address challenges and opportunities of the greatest relevance, here in New York, across