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of using and developing Machine learning/AI based classifiers Proficiency in coding using R and Python and other similar languages High level analytical capability Ability to communicate complex information
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inversion of gravity gradient data, contribute to the development of data interfaces for multi-modal sensor integration, and perform advanced data processing and inference to support subsurface imaging and
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history, economics, economic geography) and normally, a higher degree relevant to research area or equivalent qualifications High level analytical capability Ability to communicate complex information
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recognised and encompasses a broad range of Earth Science disciplines (geoscience, hydrogeology, geodata analytics, oceanography, and in Coastal and Ocean Engineering (hydrodynamics, geotechnics). Fundamental
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UKESM1 or similar models, advanced data analysis and machine learning, would be advantageous. Grade E: You will be near completion of a relevant PhD or have equivalent research experience, and be able
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analytics, oceanography, and in Coastal and Ocean Engineering (hydrodynamics, geotechnics). Fundamental and applied research is strongly tied to terrestrial and marine environments and resources, and
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of Chemistry in the College of Arts + Sciences at Indiana University, consists of a well-rounded research community with cutting-edge expertise in a wide variety of modern disciplines including analytical
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and Data Analytics in Air Traffic Management Systems. The selected candidate will work on developing innovative optimization and Machine Learning models to address key challenges in the future airspace
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. The successful candidate will work in close association with teams consisting of laboratory-based and clinical researchers to deliver the project. Experience with analysis of transcriptomic data is essential. Role
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-economic analysis and life cycle assessment methodologies. • Proficiency with modelling and simulation software relevant to TEA and LCA. • High analytical ability to analyse and illuminate data