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, spatial statistics, machine learning approaches, large ecological datasets Previous experience with passive acoustic monitoring and/or eBird data Familiarity with ecology and/or ornithology Demonstrated
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genomics modalities Background in immunology or inflammatory disease Experience with machine learning methods applied to large data Background in immunology, infectious disease, or inflammatory disease
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and/or case-crossover analyses, and have a promising publication record. Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization
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. • Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization, and a high level of independence with a publication record to support these
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laboratory team focused on improving dairy cattle nutrition and milk production efficiency and reducing enteric methane emissions. The successful applicant will be charged with managing large data sets derived
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the eBird project, one of the largest sources of avian biodiversity information in the world. The eBird team is a collaborative and innovative group that includes staff with deep expertise in bioinformatics
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information for academic references (up to 3). Application package should be emailed as one pdf file to Dr. Ke Wang at [email protected]. Please direct any questions about this position to the same email
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depth in some of the following areas (not all are required): Large-scale data analysis and learning analytics methods Experimental or quasi-experimental design; validity and measurement Working with LLMs
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Statistical and/or machine learning approaches to weather prediction Risk assessment and catastrophe modeling High-performance computing and large dataset manipulation The position involves close collaboration
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prediction Risk assessment and catastrophe modeling High-performance computing and large dataset manipulation The position involves close collaboration with industry partners in climate risk assessment