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collaboration that has mapped emotional hotspots in four cities in the UK and EU using spatial analysis of social media data. The next phase of the project aims to incorporate explainable AI (XAI) to interpret
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experience, will work as part of a larger team to assist with collecting and analyzing data gathered from human subjects, both in field, clinic and lab studies as part of evaluations of the technology. A large
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questions in human disease and health. Our work focuses on Alzheimer’s disease, cancer, and heart disease, which could have a major impact in identifying real-world big data-driven diagnostic biomarkers and
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of Carbon Dioxide (GETCO₂). At our Computational Multiphysics Laboratory (CML), we value innovation, collaboration, and technical excellence. You will benefit from access to large-scale high performance
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visualization, geospatial analysis, and processing of large amounts of meteorological and remote sensing data. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a
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of custom computer code, and the processing of large-scale simulations using massively parallel resources such as NERSC and Raj cluster at Marquette. Conduct research with a significant degree of independence
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-iu-chemistry-harnesses-advanced-computing-capabilities Our facilities used in theory are state of the art, including our Top 300 computer cluster Big Red 200, in addition to other clusters with
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++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous. Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large
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opportunity to contribute to globally impactful research. About you Doctoral Qualification in Public Health or a relevant health discipline. Project Management Experience in large-scale research across
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February 2025) that has mapped emotional hotspots in cities using spatial analysis of social media data. Our next effort aims to incorporate explainable AI (XAI) to interpret and explain spatial patterns