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Field
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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, consisting of a helium-filled aerodynamic kite tethered to an autonomous ground vehicle. Multiple vehicles operating together will create high resolution maps of emissions and airflow, at unprecedented spatial
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patients and cancer-free individuals, and will integrate these data alongside other data modalities (e.g., patient outcomes, functional genomics) to enable new clinically relevant discoveries across multiple
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researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
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an autonomous, mobile gas flux tower, consisting of a helium-filled aerodynamic kite tethered to an autonomous ground vehicle. Multiple vehicles operating together will create high resolution maps of emissions
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an advanced AI-augmented digital platform (AiCT-Med) powered by cutting edge machine learning models trained on multiple large, aged care datasets from providers across Australia. The platform is designed
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, improving prediction of evolutionary trends, and integrating multiple data types for enhanced surveillance. Gaining advanced training in the use of bioinformatics platforms, phylogenetic and phylodynamic
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(VS) has a complex ecology with multiple vector species, host species, and a wide geographic range, occurring every year in southern Mexico and semi-periodically spreading northwards to cause outbreaks
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multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and their dynamics. Conducting literature searches, manuscript preparation, and
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• Proficiency in at least one statistical software (e.g., R, Stata, SPSS, Python) • Expertise in quantitative analysis, with preferred skills in o Quasi-experimental evaluation techniques (e.g., Difference-in