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Learning methods for modeling spatial and spatio-temporal data, including point pattern data, possibly observed over complex domains. The candidate will specifically consider physics-informed statistical
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Engineering is seeking an employee in the field of remote sensing, geographic information systems and spatial planning with a desire to improve his/ her professional qualifications in the field of geographic
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also collaborate with student research assistants and postdoctoral associates. Data for these projects is accessed through the Federal Statistical Research Data Center (FSRDC), which requires
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statistical and quantitative modelling. The successful candidate will contribute to projects on flow-ecology relationships and habitat suitability modelling for freshwater organisms and will be comfortable
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science, machine learning and artificial intelligence, spatial statistics and environmental statistics, and statistical genetics and genomics. For more information, see http://www.stat.purdue.edu/ . Job
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disparities, and/or population aging. Candidates giving attention to spatial disparities or dimensions of these issues are encouraged to apply, though it is not a requirement. The successful candidate will also
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-dimensional catalog of approximately 30 million galaxies to analyze their spatial distribution and statistical properties, measuring the fundamental cosmological parameters that govern the evolution
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society are required. Knowledge and skills of GIS and spatial studies are considered advantageous. To apply, please submit your application at https://careers.purdue.edu and include the following materials
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, validate, and operationalize advanced spatial and spatio-temporal statistical methods for mapping and analysing neglected tropical diseases (NTDs). These methods will enhance the precision of disease
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and statistical consulting from experimental design to publication, resulting in close collaborations with experimentalists in every stage of the way. We have an outstanding record of publications in